bluuebunny/crossref_metadata_2025_split huggingface dataset:
Particle Handling in Particle-Based Pumped Thermal Energy Storage
Authors: Jeong Shin Young , Hirschey Jason , Shah Munjal , Gifford Jeffrey , Martinek Janna , Ma Zhiwen 
Published: September 2024

Abstract
A novel pumped thermal electricity storage system utilizes low-cost solid particles as storage media that can deliver high-temperature heat and generate power by a high-efficiency power cycle. A counterflow direct contact gas/particle fluidized bed heat exchanger is a key component in the storage system, facilitating efficient heat transfer between high-temperature media and working fluids. A comprehensive hydrodynamic analysis of the particle fluidized bed within the heat exchanger has been conducted, optimizing key parameters such as pressure drops, air superficial velocities, minimum fluidization velocities, and fluidization regimes. To ensure optimal fluidization conditions, an air distributor has been designed and fabricated. Particle handling mechanical systems that efficiently deliver particles at high temperatures are essential in the thermal storage system. Components such as L-valve, screw conveyor, and pneumatic conveyer were designed, fabricated, and tested for a prototype laboratory-scale fluidized bed heat exchanger system.
Facility LED Lighting System Upgrades With Constant Illumination Consideration
Authors: Guo Qi , Zhang Qinhe , Rosti Firouz , Zhao Cunzhi 
Published: September 2024

Abstract
This paper delves into the challenges encountered during the transition from traditional lighting to energy efficient LED lights during facility lighting system upgrades. An issue of particular concern arises when these lights are replaced on a one-to-one basis. This practice often leads to excessive brightness, resulting in problems such as employee discomfort and light pollution. To address this challenge, the paper proposes a systematic approach based on the constant illumination principle. This method aims to accurately determine the optimal quantity of lights needed during the upgrade process.
To illustrate the efficacy of the proposed approach, two lighting system redesign scenarios are present: Plan A with T8 lights and Plan B with LED lights. These scenarios highlight the importance of employing the constant illumination approach in facility lighting redesign projects. By adopting this approach, facilities can effectively embrace LED technology and subsequently, creating a comfortable work environment and promoting environmental sustainability.
Decarbonizing the Steel Processing Industry: A MILP-Based Assessment of Electrification and Hydrogen for Hot Rolling
Authors: Zabik Gabriela , Birkelbach Felix , Hofmann René 
Published: September 2024

Abstract
The steel processing industry confronts substantial challenges in decarbonization, particularly within the hot rolling process, due to uncertainties surrounding viable clean alternatives. The industry’s heavy reliance on fossil fuels necessitates a shift towards more sustainable options. The hot rolling process currently relies on natural gas fired industrial furnaces for reheating steel. Electrification and hydrogen utilization have emerged as promising clean alternatives, yet neither has achieved full maturity nor widespread application, leaving the industry at a crossroads. This paper conducts an economic and design assessment of two decarbonization scenarios for steel rolling mills. Emphasis is placed on evaluating the impact of a highly volatile grid on overall costs and analyzing the systems’ responses to grid volatilities. One scenario involves electrification using induction heating, while the other involves a switch to hydrogen, including local production. Employing mixed-integer linear programming (MILP), our objective is to minimize total annual costs (TAC), including investment and operational costs, while considering the feasibility of decarbonization pathways. Our approach includes the introduction of storage units — battery and hydrogen storage — to enhance system flexibility. Electricity price forecasts for Austria in 2050, representing a fully renewable grid, are used and capture grid volatilities and seasonal fluctuations. Results reveal that generally, electrification proves more efficient although it poses challenges within a volatile grid due to high peak demands. Conversely, the hydrogen scenario, with an electrolysis unit and storage options, effectively balances cost fluctuations. Storage units significantly impact the hydrogen scenario, reducing costs, while in the electrification scenario battery storage offers limited cost benefits. Furthermore, CO2 avoidance costs were calculated for both systems, revealing significant expenses associated with reducing CO2 emissions.
Solar Thermochemical Carbon Dioxide Splitting Using Ceria and Iron Aluminate Foam Devices and Simulation of a Plant System for Demonstration
Authors: Nakakura Mitsuho , Koyama Yoshiko , Shibuya Sofu , Warren Kent , Weimer Alan , Farrell Tucker , Asaoka Tatsunori , Matsubara Koji 
Published: September 2024

Abstract
An international research project has been undertaken to integrate a unique solar thermal processing reactor system with ceria and iron aluminate as active redox materials for CO2 splitting. Experimental investigations for CO2 splitting were conducted using a solar simulator and tube furnace at Niigata University, followed by demonstrations using a high-flux solar furnace (HFSF) at the National Renewable Energy Laboratory (NREL) in Golden, CO. Each experimental setup consisted of foam devices composed of reticulated porous ceramic (RPC). The RPC has a full ceria or iron aluminate body. It fabricated using the replica method and subjected to a two-step redox reaction, which iteratively separated a stream of CO2 into O2 and CO. Reactivity was evaluated using CO production per mass of the reactive material. The tubular furnace yielded a CO production of 6.41 mL/g at a reduction temperature of 1600°C, showcasing a higher CO production rate and total amount than those obtained from experiments conducted with solar simulators and solar furnace setups. For iron aluminate RPC, the productivity was measured as 3.57 mL/g using HFSF at a reduction temperature of 1450°C. These results are somewhat higher than those of the previous experiment at lower reduction temperatures of 1400°C–1500°C. Additionally, the production of CO in the case of ceria RPC was compared with the steady flow model simulation, which assumed chemical equilibrium at various levels of oxygen partial pressure during the reduction process. On the basis of these results, this study proposes a solar fuel system with an open receiver that uses a high-temperature heat transfer fluid.
Optimization of Panel Spacing, Tilt Angle and Azimuth Angle for Bifacial Panels With Fixed Land Acreage and Orientation for Several United States Locations
Authors: Satheesh Sabin , Venkat Sidhanth , Mulford Rydge B. 
Published: September 2024

Abstract
Bifacial solar photovoltaic modules generate electrical power on both sides of the panel, increasing energy output. Through more effective utilization of installed surface area, bifacial panels surpass the energy generation of monofacial panels per unit installed acreage. The performance of bifacial panels largely depends on their positioning relative to the sun. Therefore, bifacial panels require specific orientations to maximize energy production. The specific challenges of bifacial modules has sparked research into the ideal spacing and orientation of bifacial panels, considering geographic location, tilt angles, and solar energy production. The present study aims to pinpoint the most favorable tilt angles, azimuth angles and panel row spacings for bifacial panels across various latitudes for a fixed array area and an adjustable array area. The core objective of this research is to maximize the electricity generated by bifacial solar panels. This involves creating a model that predicts power output for a specific location, accounting for variables like panel spacing, azimuth angle, average cell temperature, local ground reflection, and panel efficiency. The study also seeks to employ optimization to achieve peak annual power production. Methodologically, the study stratifies the solar panel array into zones, calculating the power generation capacity for a central panel in each zone. This includes factors like cell temperature, efficiency, and irradiance levels on both sides. Such calculations leverage Python APIs and packages for efficiency and accuracy. The computational model also factors in shadow effects, albedo, panel placement, and atmospheric conditions. The results reveal that an optimal power production exists for the bifacial panels with an associated optimal tilt angle, azimuth angle and panel spacing. These results are presented for a fixed array size and orientation, where the number of panels adjusts as the azimuth is varied as well as for a fixed number of panels. For New Jersey, the power output is maximized with a spacing of 2.5 meters between panels set at a 33-degree tilt and facing an azimuth of 176 degrees. Similar results are presented for a variety of locations in the United States of America. In summary, for solar farms to use land efficiently while maximizing energy generation, it is critical to consider all influencing factors — such as spacing, tilt, azimuth, and panel efficiency — comprehensively.
A Techno-Economic Analysis of a 50MWth Light-Trapping Cavity-Planar Solar Receiver Tower Capital Expenditures and its Cost Mitigation Strategies
Authors: Farias Mathew , Ma Zhiwen , Martinek Janna , Xu Ben 
Published: September 2024

Abstract
To maximize thermal efficiency, the National Renewable Energy Laboratory (NREL) has proposed a light-trapping cavity-planar receiver design intended to capture energy from reradiating surfaces. This system implements a macroscale light trapping mechanism induced by panels with triangular channels, this mechanism allows for elevated temperatures on the receiver panels and in turn the temperature of the HTF; using this design coupled with the implementation of a fluidized particle flow as the HTF, it can be expected for some components to reach a peak working temperature of nearly 1000°C cyclically throughout each day-night cycle. While these temperatures correlate to higher efficiency of the CSP tower they also demand intense thermomechanical properties from the materials used to make the receiver panels. In this analysis, we will list our assumptions to provide clarity on the significance of our calculation. This cost analysis will be conducted using a combination of both case study data and surveying industry to determine costs that are relevant to the current market trends. This analysis represents an early attempt to establish the Capital Expenditures required for a CSP tower of such design to determine the feasibility of implementing such a system in the industry.
Probing Thermal Transport in Fluidized Bed Using Modulated Photothermal Radiometry
Authors: Zhang Xintong , Adapa Sarath , Ma Zhiwen , Chen Renkun 
Published: September 2024

Abstract
In concentrated solar power (CSP) applications, fluidized bed is a promising approach for high heat transfer coefficient (HTC) solar receivers and heat exchangers. However, the complexity of multiphase mixing has made it difficult to characterize and analyze the heat transfer mechanism. This paper presents an experimental study on simultaneously characterizing heat transfer in both the near-wall and the bulk regions of a fluidized bed using modulated photothermal radiometry (MPR). The MPR is a non-contact frequency-domain technique using an intensity-modulated laser as the heat source and surface infrared emission as thermometry. The thermal penetration depth of the laser heating is varied by controlling its modulation frequency, and thus the measurement can resolve the near-wall and the bulk thermal resistances. With the MPR technique, we measured fluidized silica sands with a mean size of 164 μm in a vertical channel of 6 mm depth. Our results show that the near-wall thermal resistance is substantially increased with increasing gas velocity, which partially offsets the benefit of higher HTC brought by stronger particle mixing during the fluidization. We also used the MPR to quantify the improvement in particle-wall heat transfer in an inclined channel. We found that an 8° inclination towards the heat exchanging side led to a lower near-wall thermal resistance and a higher HTC at high gas velocities. This work demonstrates that the MPR technique is a useful tool to quantify the important near-wall thermal resistance from a bulk particle bed, which not only advances our understanding of heat transfer in fluidized beds, but may also contribute to the design of fluidized bed heat exchangers with higher HTC.
A Reinforcement Learning-Based Hierarchical Speed Control of an Infinitely Variable Transmission for Tidal Current Energy Converters
Authors: Qin Zhichang , Li Gang , Zhu Weidong 
Published: September 2024

Abstract
A tidal current energy converter (TCEC) is a device specifically designed to harness the kinetic energy present in tidal energy and convert it into stable mechanical rotational energy, which can then be used to generate electricity. The core component of the TCEC is an infinitely variable transmission (IVT), which adjusts the speed ratio to maintain a stable output speed regardless of the input speed changes caused by tidal changes. In order to ensure the efficient driving performance of the IVT system, a closed-loop control strategy based on IVT state measurement data is studied in this paper. This method can effectively track the expected output speed of the IVT system in general TCEC. Based on the proposed speed control strategy, the speed regulation of the whole IVT system under different conditions is studied in theory and simulation. These promising results could directly contribute to future research to improve the efficiency of tidal energy harvesting.
Thermal Energy Storage Conceptual Design Using Reclaimed Minerals As Heat Storage Material
Authors: Singh Ajit , Baghaei Lakeh Reza 
Published: September 2024

Abstract
Thermal energy storage (TES) plays a crucial role in energy sustainability, enabling the efficient storage and utilization of thermal energy from various sources. In this paper, we propose a novel TES system that utilizes reclaimed minerals as the heat storage medium. The system comprises a tightly packed bed of processed minerals enclosing a circular pathway for heat transfer fluid (HTF). To achieve optimal performance, we develop a computational method and algorithm to estimate the required pipe length for efficient charge and discharge cycles. The analysis encompasses various factors, including pipe length, storage material thickness, tube material, schedule, and contact resistance. Through a systematic examination of these parameters, we propose an algorithmic design for an effective pipe length tailored to the specific requirements of diverse applications in heat storage systems. A significant aspect of the proposed system is its adaptability. The system parameters, such as the temperature and mass flow rate of the HTF, can be modified based on the established effective length of the pipe. This adaptability contributes not only to increased cost-effectiveness but also to diminished energy loss in the overall energy storage system.
This research employs Computational Fluid Dynamics (CFD) modeling to simulate charge and discharge cycles, incorporating varying scenarios of pipe lengths and system parameters. By evaluating the exit temperatures of the HTF and the average temperature of the storage material at different stages, the study identifies a suitable pipe length that ensures adequate discharge time for the storage material once the cutoff temperature is achieved. This tailored approach aligns with the specific demands of diverse applications, ranging from solar power plants to industrial processes, showcasing the versatility and practicality of the proposed methodology.
Resistive Heating Catalytic Micro-Reactor Design for Process Intensified Fuel Reforming to Hydrogen
Authors: Burra Kiran Raj Goud , Sahin Murat , Gupta Ashwani 
Published: September 2024

Abstract
For the increasing demand for fuel flexibility in H2 production for fuel cells, the process intensification of fuel reforming using micro-reactors has become crucial. While prior literature has seen substantial progress in hydrocarbon fuel reforming within micro-reactors employing micro-channels, the supply of thermal energy for these endothermic reactions has faced limitations, relying on external heating, or operating in autothermal mode through partial combustion. This paper explores a novel approach by investigating the use of a thin-film catalytic heater for the development of micro-reactors. The study specifically focuses on dry methane reforming, showcasing a simplified micro-reactor where thermal energy is supplied through electric resistive heating of a thin carbon sheet with a catalyst applied to its surface. The thin catalytic heated layer resides inside the reactor, minimizing energy losses and significantly reducing the overall reactor footprint. Power input was varied from 90 W to 225 W to understand its impact on the temperature achieved inside the reactor, extent of CH4 conversion, H2 and CO yields. Fast thermal response times were achieved due to the use of carbon paper as thin film for heating. Ni/MgO impregnated onto the carbon paper was utilized as the catalytic heating element which resulted in CH4 conversions greater than 60% at temperature greater than 750 K. Influence of operating conditions such as the input molar ratio of CO2/CH4, and gas hourly space velocity (GHSV) were also investigated to understand the scope of the catalyst in this setup. High GHSVs (592,885 and 948,617 mL/(hr.gcatalyst)) were tested to understand the extent of throughput achievable using this setup. This approach demonstrates improved scope and feasibility for further intensification compared to conventionally heated microreactors. The research paves the way for more efficient and compact micro-reactors, addressing challenges associated with thermal energy supply in the context of fuel reforming processes.
A Data-Driven Surrogate Modeling Optimization Framework for the Economic Dispatch of Microturbines Using Hydrogen Blends
Authors: Thierry David , Supekar Sarang , Bhattacharya Chandrachur , Christopher Joshua , Biruduganti Munidhar , Dasgupta Debolina , Som Sibendu 
Published: September 2024

Abstract
The buildings and industrial sectors require reliable energy supply, while simultaneously mitigating greenhouse gas (GHG) emissions. This poses interesting opportunities for the use of microturbine technology for on-site energy generation using natural gas blended with electrolytic hydrogen (H2) from renewable electricity. Previous work has identified a commercial gas micro-turbine that can adopt a range of H2-Natural gas (NG) blends. In this paper, we present an economic dispatch framework for a Capstone C65 microturbine, that can deliver up to 65 kW of power using various H2-NG fuel blends to optimize for system operating costs of meeting demand for electricity in a given application. To optimize the system, multi-fidelity data obtained from a combination of experimental data and computational fluid dynamics simulations were used to create surrogate models through Gaussian Process Regressions (GPRs). Then, these models were embedded into a nonlinear optimization problem whereby the least-cost turbine dispatch strategy for a 24-hour period that meets a small commercial building power demand was found by choosing the H2-NG blends and electricity generation for multiple concurrent units while also considering purchasing electricity from the grid. Furthermore, we discuss the effects of a price on CO2 emissions on the optimal fuel blend and on-site electric generation.
Towards Improving High Spatiotemporal Weather Forecast Accuracy With Data-Driven Modeling
Authors: Sharma Shivesh , Najian Maede , Goudarzi Navid 
Published: September 2024

Abstract
This study explores the potential of mesoscale weather forecasting models, such as WRF output, characterized by high spatiotemporal resolution, to enhance the precision of initial and boundary conditions for microscale simulation model development, particularly computational fluid dynamics (CFD) models. Conventional numerical weather prediction methods face challenges in maintaining accuracy and managing escalating computational costs, particularly in proximity to urban boundaries. To address these challenges, this paper proposes a fusion of model reduction techniques and machine learning-based methods, including Artificial Neural Networks (ANN) and Recurrent Neural Networks (RNN). The research illustrates that complex flow field patterns can be effectively identified using ANNs and RNNs. Moreover, it introduces a Reduced-Order Model (ROM) as a promising approach to generating low-dimensional surrogate models having high accuracy and computational efficiency. The presented ROM algorithms, leveraging RNNs and ANNs, are modeled specifically for higher spatiotemporal resolution simulations, highlighting their capability to maintain accuracy compared to reference solutions.
Discrete Modeling of Flow and Heat Transfer in High-Temperature Gravity-Driven Granular Flows for Thermal Energy Storage
Authors: Mishra Ashreet , Abourazzouk Ouidad , Zhao Jian , Li Like 
Published: September 2024

Abstract
Gravity-driven dense granular flow can be a suitable heat transfer fluid (HTF) for high-temperature thermal and thermochemical energy storage (TES and TCES). Compared to analytical and continuum approaches, discrete element method (DEM) based modeling of granular flows can elucidate the particle-scale flow and thermal transport and is thus an attractive alternative approach. The particle-scale mechanical and flow properties such as sliding and rolling friction coefficients and restitution coefficient between particles are key input parameters for DEM simulations and they can vary with temperature. This study develops a DEM model to observe the particle flow and heat transfer characteristics of dense granular flows over a wide range of temperatures (from room temperature up to 800°C). The DEM flow and heat transfer model is validated and then further used to study the effects of particle flow properties on the local particle flow velocity and temperature profiles. Compared to room temperature (23°C) operation, the particle velocity decreases by 57.10% at the particle outlet for the case with an inlet particle temperature Tp,in = 800°C, 31.06% for Tp,in = 600°C, 16.39% for Tp,in = 400°C, and 6.14% for Tp,in = 200°C, showing the significant effect of high temperature operation. The observed inlet and outlet temperature differences are 0.0°C, 3.0°C, 13.9°C, 38.9°C, and 83.4°C for the cases with Tp,in = 23°C, 200°C, 400°C, 600°C, and 800°C, respectively. This work provides particle-scale insights into thermal transport behavior in granular flows, which are useful for designing novel particle-based heat exchangers and solar receivers and reactors.