bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Teachers’ school belongingness on their performance at the secondary school level
Authors: Farooqi Muhammad Tahir Khan , Javid Muhammad , Bashir Rabia , Bibi Sadia , Awan Sher Muhammad
Published: August 2024

The primary objective of this study was to examine the effects of teachers’ school belongingness on their performance at the secondary school level. The study was descriptive and used a quantitative approach to collect data. The study population was all public secondary school teachers in Punjab province. Sahiwal division was selected through the convenience sampling technique, having three districts (Sahiwal, Okara, and Pakpattan). A sample of 325 teachers was selected through the convenience sampling technique (159 males and 166 females). The teacher performance evaluation scale (TPES) and PSSM scale were used to gather information from secondary school instructors. SPSS-20 and Microsoft Excel were used to analyze the data. To determine the effect of teachers’ school belongingness on teacher performance, linear regression was utilized. The independent sample t-test and the ANOVA were used to determine significant differences in performance based on different demographic variables (gender and locality). The study's main findings revealed that teachers’ school belongingness significantly affects teachers’ performance at the secondary school level. Based on the findings, it was also concluded that school belonging positively affected all factors of teachers’ performance. The study indicates no significant difference between the performance of secondary school teachers based on different demographic variables (gender and locality). It was recommended to apply the model of teacher’s school belongingness in many educational contexts, including schools, colleges, and universities. This kind of study should serve as the foundation for professional education, particularly teacher education.
Exploring politeness strategies: A comparative study of speeches of American and Chinese Presidents at UNGA 78th session
Authors: Batool Saira , Noreen Asifa , Sultan Maryam
Published: August 2024

Politeness is the practical application of good manners or etiquette so as not to offend others and to put them at ease. It is a culturally defined phenomenon, and therefore what is considered polite in one culture can sometimes be quite rude or simply eccentric in another cultural context. Brown and Levinson suggested four different politeness strategies that can help to make successful conversation by avoiding face threatening acts. Aim of the present study was to explore politeness strategies proposed by Brown and Levinson [4] in the speeches of the American and Chinese presidents at UNGA 78th session. The study was a comparative analysis of politeness strategies used by presidents in their speech at UNGA. The study used mixed methods research approach for the detailed analysis and comparison of politeness strategies in the speech. In present study both quantitative and qualitative analysis were used. Both speeches were analysed qualitatively by applying Brown and Levinson theory of politeness. Excel sheets were used to analyse data quantitatively. Findings showed that American president used more politeness strategies as compared to Chinese president. It was also observed that cultural difference was the reason of difference in the use of politeness strategies by American and Chinese president in their speech.
Cyber-Bullying Impact on Young Adults; Examining Stress, Coping Mechanism and Self-Esteem
Authors: Soomra Noor Ul Ain , Ahmad Ishtiaq , Muntaha Sidra Tul , Saba Zaheen
Published: August 2024

The current study aimed to identify the relationship among Cyberbullying, stress, coping and self-esteem in young adults. A correlational study design was used with purposive sampling for data collection. An online survey method was used to collect data due to the global COVID-19 pandemic, and N = 152 students from public and private universities from around the country participated in this study. Scale of Revised Cyber-bullying Scale II (Topcu & Erdur-Baker, 2018) α =.75, perceived stress scale (Sheldon Cohen, 1994), α =.87, coping scale (Hamby et al., 2013). The Rosenberg Self-Esteem Scale (Rosenberg, 1965) α=.70 was used to assess the variables. The researcher also devised a demographic sheet. Descriptive statistics were calculated. Pearson Product Moment Correlation Analyses were computed to find a relationship among cyberbullying, stress, coping, and self-esteem. Linear regression analyses were carried out to analyse the role of cyberbullying, stress, and dealing with self-esteem. The findings of the study revealed that cyberbullying, stress, and coping predicted self-esteem, whereas coping was a significant mediator between cyberbullying and stress. This study will be helpful for the students in highlighting the issue of cyberbullying and the importance of coping, which affects their self-esteem.
Exploring talent of rural area of Azad Jammu Kashmir and academic excellence
Authors: Ahmed Waqas , Awan Sher Muhammad , Ullah Muhammad Sami , Islam Naila , Manzoor Misbah
Published: August 2024

To highlight the problems and challenges of rural areas students of Azad Kashmir to not achieving academic excellence. I used a mixed research method to use the responses of 36 respondents from districts (Neelum 15; Sudhnoti 6; Bagh 05, and Muzaffarabad 10) of AJK. The collected data was manually analyzed using descriptive techniques by mean, percentage, and frequency. Most outcomes show that financial crisis, lack of support, motivation, guidance, counseling, bad parental relationships, and most minor educational institutions are common issues. Due to this effect, many talented students fail to continue their education. The importance of this study is that gifted students are the assistants of the country. The study found that this dangerous issue could be solved if specific steps were taken.
Unlocking the secrets of workplace motivation: exploring process theories and their implications for leaders
Authors:   National School of Political and Administrative Studies SNSPA Bucharest, Romania, Akerele Olusegun Oladapo
Published: August 2024

In this article, we delve into the fascinating realm of motivation at work by exploring various process theories that shed light on why people do what they do. Imagine it as a behind-the-scenes peek into the gears that drive individuals in the workplace. We'll be unravelling three major theories—Vroom's Expectancy Theory, Adams' Equity Theory, and Locke and Latham's Goal Setting Theory. Each theory is like a unique lens offering insights into the intricate dance between thoughts, actions, and motivation. We'll stroll through the key concepts, principles, and, most importantly, how these theories can be real game changers for leaders and organizations. But, like any blockbuster, we won't shy away from discussing some critiques, pondering over their practicality, and exploring how they fit into the big picture of boosting employee motivation. So, buckle up for a journey into the psychology of workplace motivation!
Market failure and the role of public administration
Authors:   Faculty of Public Administration National University of Political Studies and Public Administration Bucharest, Romania, ACHIM Maria-Cristina
Published: August 2024

The paper is about market failure and the influence of the institutional approach on it and it started from the idea of Veblen, a great 20th century economist, who presented institutionalism as an alternative to neoclassical economics. Based on neoclassical economics, in addition to explaining how a well-functioning market leads to the maximisation of welfare, an analysis of market failure was also made. The objective of the paper is to analyse market failure based on institutional economics. In addition, it was examined to determine how institutional solutions can result in limiting certain types of market failure.
Gig economy in Romania. Insights from a preliminary qualitative study with gig workers
Authors:   National University of Political Studies and Public Administration Bucharest, Romania, BUZOIANU Corina , BÎRĂ Monica ,   National University of Political Studies and Public Administration Bucharest, Romania, IGNAt Maria ,   National University of Political Studies and Public Administration Bucharest, Romania, GHEȚU Andrei ,   National University of Political Studies and Public Administration Bucharest, Romania
Published: August 2024

The rising trend of the gig economy significantly influences the labor market and work culture, as an increasing number of individuals seek out flexible work arrangements and participate in on-demand work opportunities. This shift has profoundly impacted societies and economies, particularly in light of the COVID-19 pandemic. Additionally, new forms of work and entrepreneurship within the gig economy have disrupted conventional notions of employment and raised questions about traditional employer-employee relationships. This article presents initial findings from a qualitative study exploring the difficulties encountered by gig workers in Romania. Its objective is to understand how these challenges impact gig workers’ lives and career paths, who represent a new generation of employees. Currently, information and studies on the gig economy and gig work in Romania are limited, and therefore, extant regulatory policies and mechanisms may be adapted to answering emergent work relationships. The current research aims to emphasize the necessity of a shared conceptual framework and the development of regulations and public policies concerning the gig economy and gig work in Romania, with the aim to be instrumental to policymakers, organizations, labor market specialists, scholars, and other interested parties in enhancing their understanding of gig workers in emerging economies.
International Labour Law. International Protection of Youth and Children
Authors:   National University of Political Studies and Public Administration Bucharest, Romania, HIRJU Ionelia
Published: August 2024

The evolution of human rights, a process closely linked to human emancipation, is reflected, among other things, in the protection of workers by International Labour Law. In this case, any failure to respect it is also a failure to ensure the protection of human rights. In this paper, the protection of children and young people is the main topic addressed and is analysed from a legal and practical perspective, at international and national level, in the context of the exploitation of their labour. In this regard, when discussing about Labour Law, we must start from the terminological analysis of the term "work", with the development of the law in the late 19th and early 20th century, leading to the analysis of the legal framework. Thus, the exploitation of children at work is closely linked to other challenges that the society to which they belong is facing, such as poverty, high birth rate, poor access to education and health etc., and their exploitation impacts on the development and future of children and youth. Therefore, this paper analyses the main challenges and issues that International Labour Law faces, in the context of the protection of children and young people.
Public opinion manipulation through mass media. A study case on Gaza - Israel conflict
Authors:   Faculty of Business and Administration, University of Bucharest, Bucharest, Romania, NICĂ Andreea Claudia
Published: August 2024

This paper presents how the mass media and new communication technologies influence the formation of public opinion. The main purpose is to demonstrate that social media plays an essential role in influencing the public. By analyzing the main functions of the mass media and manipulation techniques, we will observe how these are reflected in the news about the Gaza-Israel conflict, as well as the effects they generate.
Pensamiento crítico de estudiantes del quinto año de secundaria en el área de ciencias sociales, Perú
Authors: Aranda Vásquez Santos Williams , Vergara De la Cruz Rider Gerlis , Quispe Burgos Lener Javier , Briceño Caipo Luis Alfredo
Published: August 2024

La presente investigación permite conocer el nivel de pensamiento crítico de los estudiantes del quinto año de secundaria en el Área de Ciencias Sociales. La investigación fue cuantitativa consistente en 5 textos informativos que susciten el pensamiento crítico, la muestra fue de 20 estudiantes (hombres y mujeres) con edades comprendidas entre 15 y 17 años. El diseño de estudio fue descriptivo mediante la aplicación de una prueba con 20 preguntas. Los resultados demuestran que el pensamiento crítico alcanzado, llego al 65% (13) del nivel regular, el 35% (7) en el nivel bueno, y no se encuentran estudiantes en el nivel excelente y deficiente, respectivamente. En cuanto al pensamiento crítico según la prueba aplicada, el nivel promedio alcanzado es un puntaje de 97.30 sobre 200. Se concluyó que los estudiantes no han encontrado desafíos interesantes en el estudio y adolecen de herramientas para alcanzar el pensamiento crítico, de acuerdo a la prueba de evaluación aplicada. Por lo que es necesario, diseñar metodologías de enseñanza de acuerdo a la materia de estudio; considerar el contexto en el cual se quiere enseñar; planear de acuerdo a la edad de los estudiantes y sus intereses.
The Role of Profitability in Mediating the Relationship Between Liquidity on Stock Prices for the Period 2013-2022
Authors: Putra Rizal Pradana , Mahmudi Bambang , Suryani Emma
Published: August 2024

This study explores how the Net Profit Margin (NPM) acts as an intermediary in the connection between the Current Ratio (CR) and stock returns for companies included in the LQ45 Index over the period from 2013 to 2022. The study population includes all companies within the LQ45 Index, which totals 45 firms. The LQ45 Index features a group of companies with the highest liquidity in their stock performance on the Indonesia Stock Exchange (IDX). To be included, companies must have significant market capitalization, impressive stock performance over time, and strong financial health. Consequently, the LQ45 Index is highly favored by investors. Using Purposive Sampling, the sample is limited to companies that have been continuously listed on the LQ45 Index throughout the 10-year span and have the requisite data, leading to a selection of 19 companies. Analytical methods employed include Descriptive Statistical Analysis, Multiple Linear Regression, Path Analysis, and the Sobel Test, with IBM SPSS25 used for data analysis. In this research, the Current Ratio (CR) serves as the independent variable, Stock Return is the dependent variable, and the Net Profit Margin (NPM) acts as the mediating variable. Findings reveal that the Current Ratio does not significantly impact Stock Return, the Net Profit Margin has a positive and significant effect on Stock Return, the Current Ratio negatively and significantly affects the Net Profit Margin, and the Net Profit Margin fully and significantly mediates the impact of the Current Ratio on Stock Return.
Sustainable Process Systems Engineering for Chemicals within Planetary Boundaries
Authors: Guill�n-Gos�lbez Gonzalo
Published: August 2024

The planetary boundaries (PBs) define ecological limits that are critical to preserve the stability of the Earth. Six of them have already been exceeded, which calls for urgent action to optimize industrial systems capable of operating within the safe operating space that they define for humanity. Here we discuss the challenges and opportunities of including PBs in a range of application domains in Process Systems Engineering, focusing on chemicals and fuels production and the use of mathematical programming coupled with life cycle assessment to support sustainable decision-making.
Development of Mass/Energy Constrained Sparse Bayesian Surrogate Models from Noisy Data
Authors: Adeyemo Samuel , Bhattacharyya Debangsu
Published: August 2024

This paper presents an algorithm for developing sparse surrogate models that satisfy mass/energy conservation even when the training data are noisy and violate the conservation laws. In the first step, we employ the Bayesian Identification of Dynamic Sparse Algebraic Model (BIDSAM) algorithm proposed in our previous work to obtain a set of hierarchically ranked sparse models which approximate system behaviors with linear combinations of a set of well-defined basis functions. Although the model building algorithm was shown to be robust to noisy data, conservation laws may not be satisfied by the surrogate models. In this work we propose an algorithm that augments a data reconciliation step with the BIDSAM model for satisfaction of conservation laws. This method relies only on known boundary conditions and hence is generic for any chemical system. Two case studies are considered-one focused on mass conservation and another on energy conservation. Results show that models with minimum bias are built by using the developed algorithm while exactly satisfying the conservation laws for all data.
RiNSES4: Rigorous Nonlinear Synthesis of Energy Systems for Seasonal Energy Supply and Storage
Authors: Wang Yifan , Volkmer Marvin , Hagedorn D�rthe Franzisca , Reinert Christiane , Assen Niklas von der
Published: August 2024

The synthesis of energy systems necessitates simultaneous optimization of both design and operation across all components within the energy system. In real-world applications, this synthesis poses a mixed-integer nonlinear programming (MINLP) problem, considering nonlinear behaviours such as investment cost curves and part-load performance. The complexity increases further when seasonal energy storage is involved, as it requires temporal coupling of the full time series. Although numerous solution approaches exist to solve the synthesis problems simplified by linearization, methods for solving a full-scale problem are currently missing. In this work, we introduce a rigorous method, RiNSES4, to manage the nonlinear aspects of energy system synthesis, particularly focusing on long-term time-coupling constraints. RiNSES4 calculates the upper and lower bounds of the initial synthesis problem in two separate branches. The proposed method yields feasible solutions through upper bounds, while evaluating the solution quality via lower bounds. The solution quality is iteratively enhanced by increasing the resolution for calculating upper bounds and tightening the relaxations for computing lower bounds. Both branches work simultaneously and independently, with their outcomes compared after each iteration within each branch. The iterations continue until a predefined optimality gap is reached. We apply RiNSES4 to design a photovoltaic and battery energy system, considering the seasonality of both energy supply and demand sides. In comparison with a state-of-the-art commercial solver, RiNSES4 enables to solve the MINLP synthesis problem with great temporal detail and shows high potential.
Designing for the Future: The Role of Process Design in Decarbonization and Energy Transition
Authors: Hasan M. M. Faruque
Published: August 2024

The overarching goal of process design (Figure 1) is to find technologically feasible, operable, economically attractive, safe and sustainable processing pathways and process configurations with specifications for the connectivity and design of unit operations that perform a set of tasks using selected functional materials (e.g., catalysts, solvents, sorbents, etc.) to convert a set of feed-stocks or raw materials into a set of products with desired quality at a scale that satisfies the demand. Process synthesis and integration can further screen, optimize and improve these pathways for given techno-econo-environmental targets or objectives. These objectives may include, but are not limited to, minimizing the overall investment and processing costs, minimizing the energy consumption, minimizing the emissions or wastes, maxim-zing the profit, and enhancing the safety, operability, controllability, flexibility, circularity, and sustainability, among others... (ABSTRACT ABBREVIATED)
Artificial Intelligence and Machine Learning for Sustainable Molecular-to-Systems Engineering
Authors: Dowling Alexander W.
Published: August 2024

Sustainability encompasses many wicked problems involving complex interdependencies across social, natural, and engineered systems. We argue holistic multiscale modeling and decision-support frameworks are needed to address multifaceted interdisciplinary aspects of these wicked problems. This review highlights three emerging research areas for artificial intelligence (AI) and machine learning (ML) in molecular-to-systems engineering for sustainability: (1) molecular discovery and materials design, (2) automation and self-driving laboratories, (3) process and systems-of-systems optimization. Recent advances in AI and ML are highlighted in four contemporary application areas in chemical engineering design: (1) equitable energy systems, (2) decarbonizing the power sector, (3) circular economies for critical materials, and (4) next-generation heating and cooling. These examples illustrate how AI and ML enable more sophisticated interdisciplinary multiscale models, faster optimization algorithms, more accurate uncertainty quantification, smarter and faster data collection, and incorporation of diverse stakeholders into decision-making processes, improving the robustness of engineering and policy designs while focusing on the multifaceted goals and constraints in wicked problems.
Comparative Techno-economic Assessment of Hydrogen Production, Storage and Refueling Pathways
Authors: Park Minseong , Chung Hegwon , Kim Jiyong
Published: August 2024

Hydrogen, as a clean and versatile energy carrier, holds immense promise for addressing the world�s growing energy and environmental challenges. However, hydrogen-based energy systems face challenges related to efficient storage methods, energy-intensive production, refueling processes, and overall cost-effectiveness. To solve this problem, a superstructure was developed that integrates overall technologies related to hydrogen energy transportation. This study synthesizes process pathways for hydrogen energy transportation method including energy carrier production, storage, and refueling, based on the developed superstructure. The techno-economic analysis was conducted to evaluate the performance of each transportation pathway and compare it with conventional fossil fuel transportation system. Process performance criteria, including unit production cost (UPC), energy efficiency (EEF), and net CO2 equivalent emissions (NCE), serve as indicators for process performance. By comparing technological pathways, we can propose the most economically and environmentally optimal energy refueling route. Additionally, sensitivity analyses were performed on various external factors, identifying influential variables in the decision-making process for hydrogen production, storage, and refueling strategies, while also elucidating technological limitations.
Improving Mechanistic Model Accuracy with Machine Learning Informed Physics
Authors: Farlessyost William , Singh Shweta
Published: August 2024

Machine learning presents opportunities to improve the scale-specific accuracy of mechanistic models in a data-driven manner. Here we demonstrate the use of a machine learning technique called Sparse Identification of Nonlinear Dynamics (SINDy) to improve a simple mechanistic model of algal growth. Time-series measurements of the microalga Chlorella Vulgaris were generated under controlled photobioreactor conditions at the University of Technology Sydney. A simple mechanistic growth model based on intensity of light and temperature was integrated over time and compared to the time-series data. While the mechanistic model broadly captured the overall growth trend, discrepancies remained between the model and data due to the model's simplicity and non-ideal behavior of real-world measurement. SINDy was applied to model the residual error by identifying an error derivative correction term. Addition of this SINDy-informed error dynamics term shows improvement to model accuracy while maintaining interpretability of the underlying mechanistic framework. This work demonstrates the potential for machine learning techniques like SINDy to aid simple mechanistic models in scale-specific predictive accuracy.
Biogas Valorization from a Process Synthesis Perspective: Heat and Work Integration to Maximize CO2 Conversion
Authors: Sempuga Baraka C. , Ncube Selusiwe
Published: August 2024

Biogas is often considered as a source of renewable energy, for heat and power production. However, biogas has greater promise as a source of concentrated CO2 in addition to methane, making it a rich supply of carbon and hydrogen for the generation of fuel and chemicals. In this work, we use the concept of attainable region in the enthalpy-Gibbs free energy space to identify opportunities for effective biogas valorization that maximizes the conversion of CO2. The AR concept allows us to study a chemical process without knowing the exact reaction mechanism that the species in the process use. Deriving Material Balance equations that relate a reactive process's output species to its input species is sufficient to identify process limits and explore opportunities to optimize its performance in terms of material, energy, and work. The conversion of biogas to valuable products is currently done in two steps; the high temperature and endothermic reformer step, followed by the low temperature exothermic synthesis step. We demonstrate, using Aspen Simulation, that energy integration, both heat and work, between the two steps is crucial to achieving a substantial amount of CO2 conversion. We also show how a heat pump configuration can be utilized to integrate energy between the reformer and synthesis steps against the temperature gradient by integrating external renewable energy.
Techno-Economic Analysis of Methane Production from Pulp and Paper Sludge
Authors: Hosseini Erfan , Cremaschi Selen , Jiang Zhihua
Published: August 2024

This study investigates the feasibility of valorizing pulp and pulp sludge (PPS) into methane through anaerobic digestion (AD) with a focus on techno-economic analysis (TEA). Three scenarios are evaluated: (A) the base case, (B) sludge AD with alkaline pretreatment using green liquor dregs (GLD), and (C) co-digestion with nitrogen-rich feedstocks. The evaluation is applied to a common PPS, consisting of 70% primary sludge (PS) from the primary clarifier and 30% secondary sludge (SS) from biological treatments from a kraft mill. Theoretical methane potential (TMP) is determined using the Buswell equation. The study highlights the significance of co-digestion with nitrogen-rich feedstocks in enhancing the economic viability of the AD process for PPS, providing valuable insights for sustainable waste management and resource recovery in the pulp and paper industries.
Thermo-Mechanical Exergy of a Substance in Cold Applications Approaching Absolute Zero
Authors: Adams Thomas A.
Published: August 2024

In this work, we consider the thermo-mechanical exergy of a substance for cold applications, even as it approaches absolute zero. This is relevant for cold-service applications such as refrigeration, liquefied natural gas, air separation, and liquid hydrogen. We demonstrate how the optimization formulation for the determination of exergy is the most suitable way for process systems engineers to think about exergy. We provide an illustrative example by computing thermo-mechanical exergy of neon approaching absolute zero. We also discuss how this result relates with the Third Law of Thermodynamics, both how it is used to compute thermo-mechanical exergy, but also what it implies about the validity of the results and the equations used to compute them.
Integration of Design and Operation with Discretization Error Control
Authors: Hoffmann Christian , Esche Erik , Repke Jens-Uwe
Published: August 2024

Optimization-based process design is a central task of process systems engineering. However, solely relying on steady-state models may potentially lead to dynamic constraint violations, hinder robust performance, or simply reduce the controllability of a process. This has led to the consideration of process dynamics in the design phase, which is commonly termed integration of design and operation / control. Recently, we proposed a framework to carry out this integrative task by formulating a large-scale nonlinear programming problem that is solved simultaneously. To this end, the dynamic process model was discretized, and dynamic variability and parametric uncertainty were included. However, the proposed framework only operates on constant lengths of the finite elements. The discretization error was not assessed. Within this contribution, a method for quantifying this discretization error and adapting the number of finite elements accordingly is incorporated into the recently proposed framework and applied on the case study of a continuous tank reactor. The obtained results with and without discretization error control are compared and, based thereon, a more suitable way to apply the control variables on the process is proposed.
Optimal Process Synthesis Implementing Phenomena-based Building Blocks and Structural Screening
Authors: Krone David , Esche Erik , Skiborowski Mirko , Repke Jens-Uwe
Published: August 2024

Superstructure optimization for process synthesis is a challenging endeavour typically leading to large scale MINLP formulations. By the combination of phenomena-based building blocks, accurate thermodynamics, and structural screening we obtain a new framework for optimal process synthesis, which overcomes prior limitations regarding solution by deterministic MINLP solvers in combination with accurate thermodynamics. This is facilitated by MOSAICmodeling�s generic formulation of models in MathML / XML and subsequent decomposition and code export to GAMS and C++. A branch & bound algorithm is implemented to solve the overall MINLP problem, wherein the structural screening penalizes instances, which are deemed nonsensical and should not be further pursued. The general capabilities of this approach are shown for the distillation-based separation of a ternary system.
Model Diagnostics for Equation-Oriented Models: Roadblocks and the Path Forward
Authors: Lee Andrew , Parker Robert B. , Poon Sarah , Gunter Dan , Dowling Alexander W. , Nicholson Bethany
Published: August 2024

Equation-Oriented (EO) modeling techniques have been gaining popularity as an alternative for simulating and optimizing process systems due to their flexibility and ability to leverage state-of-the-art solvers inaccessible to many procedural modeling approaches. Despite these advantages, adopting EO modeling tools remains challenging due to the significant learning curve and effort required to build and solve models. Many techniques are available to help diagnose problems with EO process models and reduce the effort required to create and use them. However, these techniques still need to be integrated into EO modeling environments, and many modelers are unaware of sophisticated EO diagnostic tools. To survey the availability of model diagnostic tools and common workflows, the U.S. Department of Energy�s Institute for the Design of Advanced Energy Systems (IDAES) has conducted user experience interviews of users of the IDAES Integrated Platform (IDAES-IP) for process modeling. The interviews reveal a gap between the availability and utilization of model diagnostic tools driven primarily by a lack of awareness of and lack of standard interfaces among different tools. To address this gap, the IDAES team has developed a recommended workflow for integrating diagnostics into the model development process and an IDAES Model Diagnostics Toolbox that provides a standard interface for many of these best practices. This paper identifies barriers to the widespread adoption of diagnostic tools for EO models and reduces these barriers by providing a standard, user-friendly interface for many different tools.
Design for Flexibility: A Robust Optimization Approach
Authors: Jagana Jnana Sai , Ge Congqin , Yuan Zhihong , Amaran Satyajith , Zhang Qi
Published: August 2024

Flexibility is a critical feature of any industrial system as it tells us about the range of conditions under which the system can effectively and safely operate. It is becoming increasingly important as we face greater volatilities in market conditions, diverse customer needs, more stringent safety and environmental regulations, the growing use of resources with varying availability such as renewable energy, and an increased likelihood of disruptions caused by, for example, extreme weather... (ABSTRACT ABBREVIATED)
Design and Optimization of Circular Economy Networks: A Case Study of Polyethylene Terephthalate (PET)
Authors: Ahmed Abdulhakeem , Torres Ana I.
Published: August 2024

Circular systems design is an emerging approach for promoting sustainable development. Despite its perceived advantages, the characterization of circular systems remains loosely defined and ambiguous. This work proposes a network optimization framework that evaluates three objective functions related to economic and environmental domains and employs a Pareto analysis to illuminate the trade-offs between objectives. The US polyethylene terephthalate (PET) value chain is selected as a case study and represented via a superstructure containing various recycling pathways. The superstructure optimization problems are modeled as a mixed integer linear program (MILP) and linear programs (LPs), implemented in Pyomo, and solved with CPLEX for a one-year assessment horizon. Solutions to the circular economy models are then compared to the corresponding solutions of linear economy models. Preliminary results show that the optimal circular network is advantageous over the optimal linear network for all objectives subject to the current market supply of raw materials and the total cost of production. However, when considering the present chemical processing infrastructure of the US economy and unrestricted biomass feedstock availability, a linear economy is favorable as an outcome of low operating cost and carbon sequestration.
Role of Hydrogen as Fuel in Decarbonizing US Clinker Manufacturing for Cement Production: Costs and CO2 Emissions Reduction Potentials
Authors: Okeke Ikenna J. , Nimbalkar Sachin U. , Thirumaran Kiran , Cresko Joe
Published: August 2024

As a low-carbon fuel, feedstock, and energy source, hydrogen is expected to play a vital role in the decarbonization of high-temperature process heat during the pyroprocessing steps of clinker production in cement manufacturing. However, to accurately assess its potential for reducing CO2 emissions and the associated costs in clinker production applications, a techno-economic analysis and a study of facility-level CO2 emissions are necessary. Assuming that up to 20% hydrogen can be blended in clinker fuel mix without significant changes in equipment configuration, this study evaluates the potential reduction in CO2 emissions (scopes 1 and 2) and cost implications when replacing current carbon-intensive fuels with hydrogen. Using the direct energy substitution method, we developed an Excel-based model of clinker production, considering different hydrogen�blend scenarios. Hydrogen from steam methane reformer (gray) and renewable-based electrolysis (green) are considered as sources of hydrogen fuel for blend scenarios of 5%�20%. Metrics such as the cost of cement production, facility-level CO2 emissions, and cost of CO2 avoided were computed. Results show that for hydrogen blends (gray or green) between 5% and 20%, the cost of cement increases by 0.6% to 16%, with only a 0.4% to 6% reduction in CO2 emissions. When the cost of CO2 avoided was computed, the extra cost required to reduce CO2 emissions is $229 to $358/ metric ton CO2. In summary, although green hydrogen shows promise as a low-carbon fuel, its adoption for decarbonizing clinker production is currently impeded by costs.
Design Space Identification of the Rotary Tablet Press
Authors: Shahab Mohammad , Bachawala Sunidhi , Gonzalez Marcial , Reklaitis Gintaras , Nagy Zoltan
Published: August 2024

The determination of the design space (DS) in a pharmaceutical process is a crucial aspect of the quality-by-design (QbD) initiative which promotes quality built into the desired product. This is achieved through a deep understanding of how the critical quality attributes (CQAs) and process parameters (CPPs) interact that have been demonstrated to provide quality assurance. For computational inexpensive models, the original process model can be directly deployed to identify the design space. One such crucial process is the Tablet Press (TP), which directly compresses the powder blend into individual units of the final product or adds dry or wet granulation to meet specific formulation needs. In this work, we identify the design space of input variables in a TP such that there is a (probabilistic) guarantee that the tablets meet the quality constraints under a set of operating conditions. A reduced-order model of TP is assigned for this purpose where the effects of lubricants and glidants are used to characterize the design space to achieve the desired tablet CQAs. The probabilistic design space, which takes into account interactions between crucial process parameters and important quality characteristics including model uncertainty, is also approximated because of the high cost associated with the comprehensive experiments.
Connecting the Dots: Push and Pull between Technology R&D and Energy Transition Modeling
Authors: Federici Justin A. , Papageorgiou Dimitri J. , Nielsen Robert D.
Published: August 2024

This paper discusses the symbiotic relationship between technology research and development (R&D) and energy transition modeling. On the one hand, energy system modeling has a noteworthy history of providing macroscopic views and critical insights concerning the role that myriad technologies may play in the future energy system. On the other hand, R&D can lead to both incremental and disruptive technological advances that can shape energy transition planning. In this work, we focus on the bidirectional flow of information between the two with a particular focus on highlighting the potential role of carbon capture, storage, and sequestration technology.
Screening Green Solvents for Multilayer Plastic Films Separation
Authors: Ikegwu Ugochukwu M. , Zavala Victor M. , Lehn Reid C. Van
Published: August 2024

This paper introduces a computational framework for selecting green solvents to separate multilayer plastic films, particularly those challenging to recycle through mechanical means. The framework prioritizes the selective dissolution of polymers while considering solvent toxicity. Initial screening relies on temperature-solubility dependence, utilizing octanol-water partition coefficients (LogP) to identify non-toxic solvents (LogP = 3). Additionally, guidelines from GlaxoSmithKline (GSK), Registration, Evaluation, Authorization, and Restriction of Chemical Regulation (REACH), and the US Environmental Protection Agency (EPA) are employed to screen for green solvents. Molecular-scale models predict temperature-dependent solubilities and LogP values for polymers and solvents. The framework is applied to identify green solvents for separating a multilayer plastic film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). The case study demonstrates the framework's effectiveness in identifying environmentally friendly solvents and balancing trade-offs between solvent toxicity and solubility. Furthermore, the framework informs process design by screening for suitable green solvents in selective dissolution processes, potentially leading to the development of more sustainable dissolution processes and the identification of easily recyclable polymer blends in multilayer plastic films.
Preliminary Examination of the Biogas-to-Hydrogen Conversion Process
Authors: Chung Hegwon , Park Minseong , Kim Jiyong
Published: August 2024

Biogas is a promising energy source for sustainable hydrogen production due to its high concentration of CH4. However, determining the optimal process configuration is challenging due to the uncertainty of the fed biogas composition and the sensitivity of the operating conditions. This necessitates early-stage evaluation of the biomass-to-hydrogen process's performance, considering economics, energy efficiency, and environmental impacts. A data-driven model was introduced for early-stage assessment of hydrogen production from biogas without whole process simulation and optimization. The model was developed based on various biogas compositions and generated parameters for mass and energy balance. A database of unit processes was created using simulation models. Sensitivity analysis was performed under four techno-economic and environmental evaluation criteria: Unit Production Cost (UPC), Energy Efficiency (EEF), Net CO2 equivalent Emission (NCE), and Maximum H2 Production (MHP). The early-stage evaluation of the biogas-to-hydrogen process can guide the establishment of biogas utilization strategies and propose effective biogas enhancement process development solutions to respond to market disturbances.
Beyond Yield: Assessing Reaction System Performance using Economics
Authors: Katebah Mary A. , Al-Rawashdeh Ma�moun , Linke Patrick
Published: August 2024

Early stage exploration of reaction systems, including catalyst selection, operating conditions� specifications, reactor design, and optimization, is critical in the engineering field. It is general practice in the reaction engineering field to explore systems against certain performance metrics, of which yield is one of the most commonly utilized objectives. While the yield provides a quantitative measure of how efficiently reactants are converted into target product(s), its definition is ambiguous, particularly in the presence of side/ incomplete reactions, and multiple products. Most of the yield definitions focus on a specific target product; however, conditions within the reactor search space that provide a maximum yield for one product may not be the same as those for another. Moreover, the presence of other undesired products that are not considered may reduce the overall efficiency of the system. This necessitates the utilization of a more holistic metric that encompasses the value of all the generated products. Attempts to address this consider lumping components into a total yield metric. However, this assumes equal weights on all components without adequately capturing their individual significance on the actual performance. This study proposes the utilization of an �economic-value yield� objective that captures all the products� value by using the market price as a weight factor. The traditional yield metric for the various products is contrasted against the economic one to highlight its ability of providing insight into regions within the reactor search space that are associated with high-value products that are otherwise not observed in the conventional definition. This is illustrated with a case study utilizing propane as a feedstock in the novel piston reactor technology.
Biofuels with Carbon Capture and Storage in the United States Transportation Sector
Authors: Geissler Caleb H. , Maravelias Christos T.
Published: August 2024

There is a need to drastically reduce greenhouse gas emissions. While significant progress has been made in electrifying transport, heavy duty transportation and aviation are not likely to be capable of electrification in the near term, spurring significant research into biofuels. When coupled with carbon capture and storage, biofuels can achieve net-negative greenhouse gas emissions via many different conversion technologies such as fermentation, pyrolysis, or gasification to produce ethanol, gasoline, diesel, or jet fuel. However, each pathway has a different efficiency, capital and operating costs, and potential for carbon capture, making the optimal pathway dependent on policy and spatial factors. We use the Integrated Markal-EFOM System model applied to the USA, adding a rich suite of biofuel and carbon capture technologies, region-specific CO2 transportation and injection costs, and government incentives from the Inflation Reduction Act. We find that under current government incentives, biofuels and carbon capture from biorefineries are primarily focused in the Midwest and South of the USA, but play a relatively small role in the overall USA transportation sector even in 2055. However, increased government incentives, biomass availability, or oil price could lead to increased biofuel production and reduced transportation emissions.
Guaranteed Error-bounded Surrogate Framework for Solving Process Simulation Problems
Authors: Aras Chinmay M. , Iftakher Ashfaq , Hasan M. M. Faruque
Published: August 2024

Process simulation problems often involve systems of nonlinear and nonconvex equations and may run into convergence issues due to the existence of recycle loops within such models. To that end, surrogate models have gained significant attention as an alternative to high-fidelity models as they significantly reduce the computational burden. However, these models do not always provide a guarantee on the prediction accuracy over the domain of interest. To address this issue, we strike a balance between computational complexity by developing a data-driven branch and prune-based framework that progressively leads to a guaranteed solution to the original system of equations. Specifically, we utilize interval arithmetic techniques to exploit Hessian information about the model of interest. Along with checking whether a solution can exist in the domain under consideration, we generate error-bounded convex hull surrogates using the sampled data and Hessian information. When integrated in a branch and prune framework, the branching leads to the domain under consideration becoming smaller, thereby reducing the quantified prediction error of the surrogate, ultimately yielding a solution to the system of equations. In this manner, we overcome the convergence issues that are faced by many simulation packages. We demonstrate the applicability of our framework through several case studies. We first utilize a set of test problems from literature. For each of these test systems, we can find a valid solution. We then demonstrate the efficacy of our framework on real-world process simulation problems.
Life Cycle and Sustainability Analyses for Designing Chemical Circular Economy
Authors: Perez David , Chea John D. , Hernandez-Betancur Jose D. , Ruiz-Mercado Gerardo J.
Published: August 2024

Sustainability and circular economy enclose initiatives to achieve economic systems and industrial value chains by improving resource use, productivity, reuse, recycling, pollution prevention, and minimizing disposed material. However, shifting from the traditional linear economic production system to a circular economy is challenging. One of the most significant hurdles is the absence of sustainable end-of-life (EoL)/manufacturing loops for recycling and recovering material while minimizing negative impacts on human health and the environment. Overcoming these challenges is critical in returning materials to upstream life cycle stage facilities such as manufacturing. Chemical flow analysis (CFA), sustainability evaluation, and process systems engineering (PSE) can supply chemical products and processes performances from environmental, economic, material efficiency, energy footprint, and technology perspectives. These holistic evaluation techniques can improve productivity, source material reduction, reuse, recycling, and prevent and minimize releases and disposal rates. Therefore, this contribution offers a computational framework that covers CFA, sustainability assessment, and risk evaluation for quantifying the benefits and challenges of chemical circular economy routes versus conventional linear systems. Finally, this contribution shows promising techniques and challenges for employing CFA, sustainability evaluation, and PSE as multicriteria decision-making tools for designing a closed-loop chemical management infrastructure and transforming the US chemical industry sector from linear to circular.