bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Personnel Availability and Competency on Fleet Readiness
Authors: Colosi Lindsey , Rothrock Ling , Barton Russell , Banks Jeffrey , Reichard Karl 
Published: March 2024

The planning of future operations is a complex process that requires knowledge and understanding of many different factors and resources. Although there is much literature on maintenance planning, existing work lacks the integration of robust personnel work schedules into scheduling algorithms. Thus the objective of this research is to develop a procedure that aids in the short- term planning of operations by predicting the future readiness level of a fleet of vehicles that are subjected to various personnel factors. This research presents a procedure that combines two different models to appropriately predict readiness levels at the end of a seven-period horizon. This first model is a Monte Carlo simulation that determines different personnel availability scenarios based on three different factors that affect the net resource pool of workers of a maintenance unit. These scenarios are then entered into a binary integer linear program (BILP) which literatively optimizes fleet maintenance schedules on a daily basis. An overall fleet readiness level with a certain degree of probability is determined which serves as an extremely useful tool for operations planning. In addition, sensitivity analysis is presented on the different factors affecting personnel availability that can serve as useful aids in operational decision-making.
Detection of Precursors to Component Failure in a Spur Gear Drive-Train by Means of a Torque Transducer
Authors: Yutzy Joseph , Bruns Christopher , Yoder Nathanael , E. Adams Douglas , Gul Kamran , Calhoun Keith 
Published: March 2024

In the wind energy industry, gearbox failures are among the most costly and the most frequent, adding significantly to the operation and maintenance costs over the life cycle of the turbine. Despite significant improvements in the understanding of gear loads and dynamics, even to the point of establishing international standards for design and specifications of wind turbine gearboxes, these components generally fall short of reaching their 20 year design life. In a significant number of gearbox failures, the primary bearing on the low speed shaft experiences faults in its operation, such as misalignment and movement on the mounts. To investigate the topic of gear health management, a fault detection approach is applied to a test bed involving a spur gear double-reduction transmission, outfitted with a torque transducer and triaxial accelerometers on the bearing cases. The test bed is not a wind turbine gearbox – the gear arrangement is different and the gears are smaller compared to that of a typical wind turbine gearbox – but it does serve to test the modeling and fault detection methods proposed in this paper. Both baseline and faulted measurements are taken from the experimental set-up for data analysis. It is shown that the torque sensor provides an early indication of fault precursors, such as misalignment and decreased lubrication, while also maintaining the capacity to identify mature faults, such as chipped and missing gear teeth. The measurements are analyzed using statistical based methods – the Mahalanobis distance and Parzen discriminant analysis. These features for fault detection are then characterized at various operating speeds for each of the geartrain conditions of interest. An analytical model is created from first principles for verification of results and for simulation of the free and forced dynamics of the system.
Combination of analytical and statistical models for dynamic systems fault diagnosis
Authors: Bregon Anibal , Garcia-Alvarez Diego , Pulido Belarmino , Jesus Fuente Maria 
Published: March 2024

Complex industrial and aerospatial systems require efﬁcient monitoring and fault detection schemes to ease prognosis and health monitoring tasks. In this work we rely upon the model-based approach to perform robust fault detection and isolation using analytical and statistical models. We have combined Principal Component Analysis (PCA) together with Possible Conﬂicts (PCs), to improve the overall diagnosis process for complex system. Our proposal uses residuals computed using PCs as the input for the PCA tool. The PCA tool is able to accurately determine signiﬁcant deviations in the residuals, that will be identiﬁed as faults. The integration of both techniques provides more robust results for fault detection, while avoiding false alarms in PCAs due to changes in operation modes. Moreover, it provides the PCA approach with the necessary mechanisms to perform fault isolation. This approach has been tested on a laboratory plant with real data, obtaining promising results.
Online Monitoring of Plant Assets in the Nuclear Industry
Authors: Agarwal Vivek , J. Lybeck Nancy , T. Pham Binh , Rusaw Richard , Bickford Randall 
Published: March 2024

Today’s online monitoring technologies provide opportunities to perform predictive and proactive health management of assets within many different industries, in particular the defense and aerospace industries. The nuclear industry can leverage these technologies to enhance safety, productivity, and reliability of the aging fleet of existing nuclear power plants. The U.S. Department of Energy’s Light Water Reactor Sustainability Program is collaborating with the Electric Power Research Institute’s (EPRI’s) Long- Term Operations program to implement online monitoring in existing nuclear power plants.
Proactive online monitoring in the nuclear industry is being explored using EPRI’s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software, a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. This paper focuses on development of asset fault signatures used to assess the health status of generator step-up transformers and emergency diesel generators in nuclear power plants. Asset fault signatures describe the distinctive features based on technical examinations that can be used to detect a specific fault type. Fault signatures are developed based on the results of detailed technical research and on the knowledge and experience of technical experts. The Diagnostic Advisor of the FW-PHM Suite software matches developed fault signatures with operational data to provide early identification of critical faults and troubleshooting advice that could be used to distinguish between faults with similar symptoms. This research is important as it will support the automation of predictive online monitoring
A New Prognostic Approach for Hydro-generator Stator Windings
Authors: Amyot Normand , Hudon Claude , Lévesque Mélanie , Bélec Mario , Brabant France , Frenette François-Xavier 
Published: March 2024

Significant improvements in hydro-generator diagnostics were achieved, in the past decades, by using continuous online measurements and a number of periodic tests. In recent years, the diagnostic raw data has been converted into more useful information by way of integrated diagnostic systems that used expert knowledge. For example, an integrated methodology for hydro-generator diagnostics was developed at Hydro-Québec’ s research institute (IREQ) using a Web-based application. This comprehensive diagnostic system gives the degradation state of generator stator winding insulation by using a portfolio of diagnostic tools. Combining the results leads to a health index ranging from 1 (good condition) to 5 (worst condition). This system is used by Hydro-Québec’s power plant managers as well as technical support and maintenance engineers in the context of condition-based maintenance (CBM). The next step of development is to add new prognostic-related features. This involves automatic identification of active failure mechanisms, root cause analysis and estimation of the stage of advancement of any active mechanism. These characteristics form the basis of predictive maintenance and support the optimization of maintenance strategies.
The approach is based on a number of causal trees (the failure mechanisms) formed by the combination of sequential physical degradation states that ultimately lead to a failure mode. Each combination of sequential physical states is unique and defines a particular failure mechanism. Failure mechanism analysis was followed by identification of all symptoms (diagnostics measurements, observations) with their respective thresholds defining each physical state.
This paper presents the development of a prognostic approach where the modeling of failure mechanisms is combined with observable symptoms from our diagnostic system for the identification of active failure mechanisms.
Determination of Primary Chemical Constituents of PBX(AF)-108 Warhead Explosive Using microPHAZIRTM Near Infrared (NIR) Handheld Platform
Authors: Daoud Sami , J. Villeburn Michal , D. Bailey Kevin , Kinloch Gordon , Biegert Lydia , Gardner Craig 
Published: March 2024

An innovative prognostics and health management (PHM) technique for quantifying and characterizing health status of Plastic Bonded Explosive (PBX) Air force (AF) formula PBX (AF)-108 warhead explosive was developed using Near Infrared (NIR) spectra emitted by microPHAZIRTM NIR, a handheld platform developed by Thermo Fisher Scientific. Benchtop High Performance Liquid Chromatography (HPLC) was used as a reference technique for correlation to microPHAZIRTM NIR measurements.
Near infrared spectra were acquired from twenty freshly manufactured mixes of PBX (AF)-108 explosive formulae, which were used in setting up a D-Optimal full-factorial design of experiment (DOE). Three-hundred and sixty measurements were recorded and analyzed using Partial Least Squares (PLS) regression analysis for model building and method development. Results were correlated to spectra, which were measured using HPLC reference technique. All recorded measurements performed with microPHAZIRTM handheld platform were successfully validated with HPLC measurements. An algorithm was developed for microPHAZIRTM NIR thus qualifying the platform as a real-time nondestructive test (NDT)/

nondestructive evaluation (NDE) tool for quantification of primary chemical constituents of PBX (AF)-108. Primary chemical constituents of PBX(AF)-108 are Polyurethane (PU) binder, Royal Demolition Explosive (RDX) oxidizer/ fuel, Isodecyl Pelargonate (IDP) plasticiser, and E-702 (4, 4’-methylenebis(2,6-di-tert-butyl-phenol) [MBDTBP] anti- oxidant/stabilizer.
This teaming effort between Raytheon Missile Systems (RMS), United Kingdom Ministry of Defence (UK MoD), Alliant Techsystems Launch systems (ATK LS), and Thermo Fisher Scientific demonstrated outstanding ability to utilize miniature cutting edge technology to perform real- time NDT of PBX (AF)-108 warhead explosive without generating chemical waste and/or residue. The new technique will further be adapted for use to measure primary chemical constituents of other warhead explosives and solid rocket propellants. The new technique will significantly reduce costs associated with performing ordnance surveillance and Service Life Extension Program (SLEP) assessment, which is often destructive and requires use of lengthy and expensive test techniques described in North Atlantic Treaty Organization (NATO) Standardization Agreement (STANAG)-4170 and Allied Ordnance Publication (AOP)-7 manuals.
Modeling Degradation Using Thermodynamic Entropy
Authors: D. Bryant Michael 
Published: March 2024

Manufacture transforms raw materials into finished components. Ageing and degradation of components, driven by dissipative processes, irreversibly alter material structures. The second and third laws of thermodynamics assert that these dissipative processes must generate entropy. This entropy is a fundamental quantity to describe ageing and degradation.
This recognition led to a Thermodynamic Degradation Paradigm encapsulated in a Degradation Entropy Generation (DEG) Theorem, wherein the rate of degradation was related to the irreversible entropies produced by the underlying dissipative physical processes that age and degrade components. This paradigm and theorem permit a structured approach to modeling degradation of any kind. If properly applied, the DEG Theorem leads to a differential equation in a variable that describes the degradation. The equation depends on the operational and environmental variables that characterize the system. Integration of the equation accumulates the degradation over time. This approach has led to accurate models for progression of and failure by wear, fatigue, and battery degradation that are consistent with prior models.
This article will review the Thermodynamic Degradation Paradigm and Degradation Entropy Generation Theorem, and apply these to formulate predictive models of wear, fatigue, and battery degradation, i.e., differential equations that govern the degradation or ageing. The article will conclude with a discussion on how to use these governing degradation equations for machine prognosis.
A V-Diagram for the Design of Integrated Health Management for Unmanned Aerial Systems
Authors: E Heaton Andrew , Fan Ip-Shing , K Jennions Ian , Lawso Craig , McFeat Jim 
Published: March 2024

Designing Integrated Vehicle Health Management (IVHM) for Unmanned Aerial Systems (UAS) is inherently complex. UAS are a system of systems (SoS) and IVHM is a product- service, thus the designer has to take into account many factors, such as: the design of the other systems of the UAS (e.g. engines, structure, communications), the split of functions between elements of the UAS, the intended operation/mission of the UAS, the cost verses benefit of monitoring a system/component/part, different techniques for monitoring the health of the UAS, optimizing the health of the fleet and not just the individual UAS, amongst others. The design of IVHM cannot sit alongside, or after, the design of UAS, but itself be integrated into the overall design to maximize IVHM’s potential.
Many different methods exist to help design complex products and manage the process. One method used is the V- diagram which is based on three concepts: decomposition & definition; integration & testing; and verification & validation. This paper adapts the V-diagram so that it can be used for designing IVHM for UAS. The adapted v-diagram splits into different tracks for the different system elements of the UAS and responses to health states (decomposition and definition). These tracks are then combined into an overall IVHM provision for the UAS (integration and testing), which can be verified and validated. The stages of the adapted V-

diagram can easily be aligned with the stages of the V- diagram being used to design the UAS bringing the design of the IVHM in step with the overall design process. The adapted V-diagram also allows the design IVHM for a UAS to be broken down in to smaller tasks which can be assigned to people/teams with the relevant competencies. The adapted V-diagram could also be used to design IVHM for other SoS and other vehicles or products
A data pipeline for PHM data-driven analytics in large-scale smart manufacturing facilities
Authors: Odonovan Peter , Leahy K. , Cusac D. Og , Bruton K. , J. O’Sullivan D. T. 
Published: March 2024

The term smart manufacturing refers to a future-state of manufacturing, where the real-time transmission and processing of information across the factory will be used to produce advanced manufacturing intelligence that can optimize every aspect of its operation. In recent years, initiatives and groups such as the Smart Manufacturing Leadership Coalition (SMLC), Industry 4.0, and the Industrial Internet Consortium (IIC), have led the way by bringing together industry, academia and government to establish policies, roadmaps and platforms to support smart manufacturing. Although there are many characteristics that can be associated with smart manufacturing across these initiatives, a common theme is the emphasis on transitioning operations from reactive and responsive, to predictive and preventative. The research presented in this paper focuses on the development of a data pipeline that supports the development of data-driven Prognostics and Health Management (PHM) applications. In the context of smart manufacturing, PHM enables facilities to transition from preventative and reactive maintenance strategies, to predictive, preventative and condition-based strategies. The benefits that can be derived by PHM are aligned with those of smart manufacturing, which include the opportunity to decrease costs, increase machine availability, reduce energy consumption, and improve production yield.
However, the process of ingesting, cleaning and transforming real-time data streams for data-driven PHM is a difficult, complex and time-consuming task, with estimates from business intelligence projects ranging from 80% to 90% of total project effort. This effort may only be exacerbated further in manufacturing environments due to additional technology challenges, such as low levels of standardization, disparate protocols and interfaces, and ad hoc data management. While emerging technologies such as Cyber Physical Systems (CPS) and Internet of Things (IoT) can overcome many of these challenges and provide an open platform for transmitting data, existing large-scale manufacturing facilities that are subject to compliance, regulation, and stringent quality

assurance policies may not be able to adopt these technologies in the short-term due to the associated cost, risk and effort. Therefore, PHM applications that need to access data streams in large-scale manufacturing facilities must do so using transparent data integration that does not discriminate between emerging and legacy technologies in the factory. To this end, this research presents a real- time, scalable, robust, and fault tolerant data pipeline for ingesting, cleaning, transforming, processing and contextualizing time-series data from a wide-range of sources in the factory.
Reducing Tachometer Jitter to Improve Gear Fault Detection
Authors: Bechhoefer Eric , He Dave 
Published: March 2024

Much research has been published on gear fault analysis techniques, almost all based on the time synchronous average (TSA). These include and are not limited to: residual analysis, energy operator, energy ratio, amplitude modulation, frequency modulation, sideband index, zeroorder figure of merit, etc. Because the TSA is based on tachometer zero cross times for a key phasor, the performance of these analyses is dependent on the quality of the tachometer data. The tachometer signal always has jitter, due to electrical noise, magnetic noise, or manufacturing spacing error of the tachometer target (e.g. gear tooth spacing). By implementing a novel zero phase filter to reduce tachometer jitter, large improvements in the fault detection were observed. For a known gear fault, the separability, related to fault detection, increased from 10 to 25%.
Pregnant Women's Knowledge on Preconceptional and Conceptional use of Folic Acid in Rania City
Authors: Khidhir Renas Mohamed , Fares Khalat Karwan , Mohammed Ribwar A. , Mohammad Zhian Abdulla 
Published: March 2024

Background and objectives: Pregnancy is one of the most important periods in the life of woman. Nutrition plays an essential role in the development of a healthy pregnancy. The importance of the taking adequate essential vitamins such as Folic acid both before and during pregnancy is emphasized for the wellbeing of a developing embryo. The purpose of this use study is to assess the level of pregnant woman’s Information regarding adherence of using folic acid supplementation in Rania City.
Methods: In a descriptive cross section study, 100 women were selected. On the basis of questionnaires and interviews, data was obtained during the month of (December, 2020 to March, 2021). Data was analyzed using SPSS Version 23.

Result: The obtained information revealed that (71%) of pregnant women had intermediate level of knowledge Although excellent knowledge of folic acid was only (14%). Doctors are major sources for promoting awareness about folic acid. There is a significant relationship between the knowledge, level of education, age group, and monthly income. There were more women with high levels of knowledge among those who had lower parities, had more education, and were looking for health-related information.
Conclusion: Results acquired have shown some understanding towards the perception of folic acid among pregnancy. Therefore, it is important to increase the awareness of folic acid supplementation among women who are or planning to become pregnant.
KEWENANGAN MAHKAMAH KONSTITUSI REPUBLIK INDONESIA DALAM MENGUJI UNDANG-UNDANG TERHADAP UNDANG-UNDANG DASAR
Authors: Amalia Dyah Silvana 
Published: March 2024

Mahkamah Konstitusi Republik Indonesia merupakan Lembaga Negara sebagai produk amandemen Ketiga UUD NRI Tahun 1945. Amandemen Ketiga tersebut menetapkan bahwa Mahkamah Konstitusi Republik Indonesia harus sudah terbentuk pada 17 Agustus 2003.
Pasal 24C ayat (1) UUD NRI Tahun 1945 menetapkan bahwa Mahkamah Konstitusi memiliki empat kewenangan dan satu kewajiban: a. menguji undang-undang terhadap undang-undang dasar, b. menyelesaikan sengketa lembaga negara yang kewenangannya diberikan oleh UUD, c. membubarkan partai politik d. menyelesaikan sengketa hasil pemilihan umum. Sedangkan satu kewajiban Mahkamah Konstitusi adalah memutus pendapat DPR bahwa Presiden atas pendapat DPR mengenai dugaan pelanggaran hukum oleh presiden dan wakil presiden menurut UUD. Namun penelitian ini hanya mendiskusikan kewenangan MK dalam pengujian undang-undang terhadap UUD.
Penelitian ini adalah penelitian hukum normative dengan menggunakan berbagai norma hukum sebagai bahan analisis. Kesimpulan diambil dengan menggunakan penafsiran hukum.
TINJAUAN HUKUM ANAK ANGKAT TERHADAP PEMBAGIAN HAK WARIS ATAU HARTA WARIS DAN WASIAT WAJIBAH
Authors: Hadiyanto Ide Prima 
Published: March 2024

Suatu permasalahan atau perselisihan ahli waris dengan anak angkat mengenai pembagian hak waris atau harta waris dari orang tua angkat. untuk mengetahui dan menjelaskan kedudukan anak angkat terhadap pembagian hak waris atau harta waris serta pelaksanaan wasiat wajibah dari Kompilasi Hukum Islam dan BW (Burgerlijk Wetboek). untuk mengetahui dan menjelaskan anak angkat mendapatkan pembagian waris atau harta waris menurut Kompilasi Hukum Islam dan BW (Burgerlijk Wetboek). Kedudukan anak angkat bedasarkan kompilasi hukum Islam yang kedudukannya hanya sebatas anak yang diangkat oleh orang tua angkatnya dan masih bernasabkan kepada orang tua kandungnya. BW (Burgerlijk Wetboek) menjelaskan bahwa anak angkat bisa mewarisi akan tetapi dengan melalui cara hibah wasiat yang dilakukan oleh orang tua angkatnya dengan tidak merugikan para ahli warisnya. Kedua: Dalam kompilasi hukum Islam dijelaskan bahwa pembagian waris atau harta waris kepada anak angkat dapat dilakukan melalui wasiat wajibah. Pembagian tersebut sebanyak sepertiga. Sedangkan pada BW (Burgerlijk Wetboek) menetapkan bahwa anak angkat mendapatkan sepertiga dari harta waris melalui hibah wasiat.
Kata kunci: anak angkat, waris, wasiat