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SSRN 2024年

作者： Tonon, Giovana Chinaglia Filho, Rubens Maciel University of Campinas School of Chemical Engineering Department of Product and Process Development Av. Albert Einstein no 500 SP Campinas13083-852 Brazil

The urgent need to mitigate greenhouse gas (GHG) emissions, as outlined in the Paris Agreement (COP21), has encouraged a global search for effective strategies. Carbon Dioxide Capture and Utilization (CCUS) has emerged as a prominent solution, aiming to substitute carbon raw materials in chemical processes with CO2, especially when coupled with hydrogen. This study focuses on the production of methanol, a pivotal platform molecule, and explores its potential as a cleaner alternative within carbon-intense industries. Additionally, the study delves into Bioenergy with Carbon Capture and Storage (BECCS), particularly in the context of Brazil's abundant ethanol production, where CO2 is a byproduct of fermentation. Despite the promise of biogenic carbon, challenges persist, especially concerning the energy-intensive reaction step. This research develops and evaluates a model to assess the impact of CO2/H2 feed ratio, pressure, and temperature on reaction performance, to optimize conversion and energy efficiency. The models achieved less than 5% error and revealed that optimal operation strategies entail increasing pressure, temperature, and feed ratio for enhanced conversion rates while reducing pressure and temperature and increasing feed ratio to improve energy efficiency. © 2024, The Authors. All rights reserved.

关键词： Optimization

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Interplay of germination time, nutritional content, bioactive constituents, antioxidant activity, and in-vitro digestibility in kodo, little, and barnyard millets

Food and Humanity

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Food and Humanity 2025年 4卷

作者： Prasad, Priyanka Sahu, Jatindra K. Food & Bio-process Engineering Lab centre for Rural Development and Technology Indian Institute of Technology Delhi New Delhi 110016 India

Kodo, little, and barnyard millets are considered as minor millets. The changes in total starch, amylose and nutritional content, bioactive constituents, antioxidant activity, starch hydrolysis kinetics, in-vitro protein digestibility, in-vitro glycaemic potential, morphology, and molecular interactions caused by different durations of germination treatment in minor millets flour were analysed. The selected millet grains were soaked and germinated at optimized conditions of temperature by standard method for 24, 48, and 72 hours. After the soaking-germination treatment, starch content of each of the selected millet flour decreased significantly (p < 0.01) with the maximum decrease after 72 hours. A significant (p < 0.05) increase in bioactive constituents and antioxidant activity assessed by DPPH RSA, FRAP, and ABTS was observed in each of the three millet flour during germination from 24 to 72 h. After soaking and germination the in-vitro protein digestibility and in-vitro glycaemic potential increased significantly (p < 0.05, 0.01). The reduced ratio of crystalline and amorphous region, particularly after 24 & 48 h of treatment in the selected millet flour suggested the loss of ordered structure. Principal component analysis revealed interactions between matrix constituents and functional properties in minor millet flours and grouping in terms of analysed properties of minor millet flours with respect to different time duration of soaking-germination treatment. © 2025 Elsevier B.V.

关键词： Antioxidant activity FTIR Germination duration Glycaemic potential Minor millets Starch hydrolysation

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Power Resilience Planning under the Threat of Artificial Intelligence

Power Resilience Planning under the Threat of Artificial Int...

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Portland International Conference on Management of engineering and Technology (PICMET)

作者： Chip Corbett Cuong Nguyen Dahm M. Hongchai Prajakta Thorat Pavithra Prasad Sarah von Schimmelmann Charles Weber Tim Anderson Engineering and Technology Management Department Portland State University Portland Oregon USA Product Development Department Allbirds Portland Oregon USA Process Engineering Department Intel Portland Oregon USA

ISBN: (数字)9781890843458

ISBN: (纸本)9798350369137

The earth is an unstable planet. Change is constant and frequently chaotic. It is very important to plan carefully to manage changes that can be anticipated now, and to cover potential issues that might not yet have been discovered. The dawn of artificial intelligence (AI) presents a host of new concerns and opportunities. The criteria for evaluation are diverse and complex. Cybersecurity is absolutely essential, yet advances in technology have created an internet of things (IoT) where threat vectors might gain access to critical command and control elements through trillions of connected IoT devices. Whereas elegant zero trust cybersecurity models can be constructed and deployed, the vast majority of successful attacks involve a human element. Disruptive change makes decisions on any future course of action very difficult to evaluate. Distributed energy resources (DERs) can be designed to benefit individuals and improve the resilience of the power grid. We propose to direct the deployment of limited resources in an efficient fashion by evaluating the multi-discipline criteria using a hierarchical decision model (HDM), evaluated by human subject matter experts (SMEs) and generative artificial intelligence (GenAI).

关键词： Subject matter experts Passwords Programming Power grids Vectors Zero Trust Planning

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Effect of Graphite Addition on Microstructure, Mechanical Properties and Thermal Properties of Injection Molded AZ91D Alloy+1

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Materials Transactions 2024年第4期65卷 374-380页

作者： Hideshima, Yasutoshi Maeda, Fumiya Fukuta, Tadao Ozaki, Koichi Course of Advanced Systems Engineering Graduate School of Computer Science and Systems Engineering Okayama Prefectural University Soja719-1197 Japan Process Technology Development Department Technology Development Division Seiko Epson Corp. Suwa399-0211 Japan Department of Systems Engineering Faculty of Computer Science and Systems Engineering Okayama Prefectural University Soja719-1197 Japan

Magnesium chips were coated with a high concentration of graphite using a binder and were used as the raw material for injection molding. The microstructure of the magnesium injection-molded product with added graphite exhibited a dispersion of needle-like graphite particles. No significant voids were observed at the interfaces between the graphite and the matrix. The addition of more than 0.5 mass% graphite decreased the proof stress and tensile strength of the injection-molded products. The Young’s modulus of the graphite-added products tended to decrease with an increase in the graphite content, which is consistent with the lower limit of the rule of mixtures. The thermal conductivity of the 6.9 mass% graphite-added product increased compared with that of the AZ91D magnesium alloy and the coefficient of linear thermal expansion decreased. Both values are within a range that satisfied the rules of mixtures. © 2024 The Japan Institute of Metals and Materials.

关键词： Thermal expansion

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Characterization of GaN-on-SiC Wafers using a Multi-Method Laser-Based Pump-Probe Technique

Characterization of GaN-on-SiC Wafers using a Multi-Method L...

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Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM)

作者： Yiwen Song Daniel Shoemaker Kyuhwe Kang Michael Schuette James S. Tweedie Scott T. Sheppard Sukwon Choi Department of Mechanical Engineering The Pennsylvania State University Pennsylvania USA RF Device and Process Development Wolfspeed Durham NC USA

Gallium nitride (GaN) high electron mobility transistors (HEMTs) are key components of modern radio frequency (RF) power amplifiers. However, device self-heating negatively impacts both the performance and reliability of GaN HEMTs. Accordingly, laser-based pump-probe methods have been used to characterize the thermal resistance network of epitaxial material stacks that are used to fabricate HEMT structures. However, validation studies of these measurement results at the device level are lacking. In the present work, a GaN-on-SiC wafer was characterized using frequency-domain thermoreflectance and steady-state thermoreflectance techniques. The thermal conductivity of the GaN channel/buffer layer, SiC substrate, and the interfacial thermal boundary resistance at the GaN/SiC interface were determined. Results were validated by performing thermal imaging and modeling of a transmission line measurement (TLM) structure fabricated on the GaN-on-SiC wafer.

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Research on PSO-SVM base wine grade recognition based on Max-Relevance and Min-Redundancy feature selection

Research on PSO-SVM base wine grade recognition based on Max...

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作者： Yang, Jiaping Ren, Dongping Liu, Yong Zhou, Hailong Sun, Yunquan Institute of Engineering and Applied Technology Fudan University Shanghai China Brewing Process Optimization Department Luzhou Laojiao Co. Ltd. Luzhou China School of Automation and Information Engineering Sichuan University of Science and Engineering Zigong China Teaching and Research Section Artificial Intelligence of Key Laboratory of Sichuan Province Zigong China Research and Development Department Luzhou Zhitong Automation Equipment Co. Ltd. Luzhou China

In response to the challenges inherent in Baijiu classification, characterized by ambiguity and limited methodologies, this study introduces a novel framework for comprehensive Baijiu brewing process management. By integrating mathematical models and machine learning algorithms, our aim is to standardize and enhance the accuracy of the Baijiu brewing process. Through a meticulous analysis of 13 input features using the MRMR algorithm, we identified key variables that significantly influence base wine grades. Subsequently, we compared the efficacy of support vector machine (SVM) algorithms under three kernel functions for base wine grading classification. Additionally, we developed an enhanced particle swarm-support vector machine (IPSO-SVM) algorithm, which incorporates nonlinearly decreasing inertia weights to enhance global and local search capabilities. Evaluation metrics, including accuracy and F1-SCORE, were employed to assess the model's performance. Our experimental results demonstrate that IPSO-SVM significantly improves convergence speed and accuracy, achieving a classification accuracy of 98.31% on the test set with an F1-SCORE of 98.18%. Furthermore, experimental tests conducted at a prominent strong-flavored wine enterprise in China validated the model's effectiveness, revealing no significant difference in grading quality between model and manual Baijiu classification, with a mean error below 1%. This study presents a pioneering approach to digitize and standardize Baijiu classification processes, laying theoretical foundations for the development of intelligent Baijiu classification systems. © 2024 John Wiley & Sons Ltd.

关键词： Wine

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A Novel Silicone Rubber for Situation Awareness 4

A Novel Silicone Rubber for Situation Awareness

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2022 4th International Conference on Advanced Materials and Ecological Environment, AMEE 2022

作者： Xia, Bing Li, Xiaofei Yang, Xiaoyan Zhang, Donghai Zhang, Miao Li, Hao Xu, Shanjun Kong, Deqing Li, Xiang Beijing Guodianfutong Science & Technology Development Co. Ltd. Beijing100071 China Nari Group Corporation State Grid Electric Power Research Institute Jiangsu Nanjing211106 China Institute of Process Engineering Chinese Academy of Sciences Beijing102401 China

An insulator plays an important role in the external insulation of power grid. The antifouling flashover coating on the insulator's surface can effectively reduce the incidence of pollution flashover accidents. Local overheating, local arc, lightning and other damage lead to the deterioration of the antifouling flashover coating, resulting in pollution flashover accidents. In order to realize the on-line identification of electric arc on the surface of antifouling flashover coating, various functional nanoparticles were prepared and added into the silicone rubber to prepare functional antifouling flashover coating. The colour deviation of the coating heated at different temperatures was measured by a spectrophotometer, and the trace of arcs on the sample surface was observed. The results show that the functional nanoparticles can slightly improve the tensile strength and AC breakdown strength of silicone rubber composites. The composites change colour in 2 min at 250°C or 1s at 500°C, showing obvious indication traces after an electric arc passes the surface of an insulator in a short period. Still, the composites possess excellent functional properties after 1000h artificial accelerated aging test. © Published under licence by IOP Publishing Ltd.

关键词： Nanoparticles

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Compact High Power Density Axial Flux PM Motor for Surgical Robotics Application

Compact High Power Density Axial Flux PM Motor for Surgical ...

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IEEE International Conference on Electric Machines and Drives (IEMDC)

作者： Madhavan Ramanujam Norbert Veignat Dipak Mane Yogesh Lulle Sandip Dhanwate Andrew Sharp Research and Development Portescap West Chester PA USA Research and Development Portescap La Chaux-de-Fonds Switzerland Design and Development Portescap Mumbai INDIA Process Quality Engineering Portescap Mumbai INDIA CAD Engineering Portescap Mumbai INDIA

Motor topologies for the surgical robotics application should have the characteristics of smoother operation at low-speed region and improved dynamic response. In addition, the motor must be lighter in weight and compact in size. To achieve these performance indices, single-sided axial flux permanent magnet motor configuration having optimal slot-pole combination with soft magnetic composite based open-slotted stator design is proposed. The stator tooth profiling is introduced to reduce or eliminate the cogging torque. Finite element-based simulation is carried out to understand the effect of the stator tooth profiling on the selected 12slot, 10pole motor configuration is presented. In addition, the prototype motor built, and motor performance is measured and analyzed. It is shown that chamfering on the stator tooth helps to reduce the cogging torque magnitude within the required specifications of 0.5mNm.

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On the use of Physics in Machine Learning for Manufacturing process Inspection 6

On the use of Physics in Machine Learning for Manufacturing ...

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Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI 2023

作者： Barbastathis, George Zhang, Qihang Pandit, Ajinkya Tang, Wenlong Papageorgiou, Charles Braatz, Richard D. Myerson, Allan S. Tan, Bingyao Schmetterer, Leopold Department of Mechanical Engineering Denmark Department of Chemical Engineering Massachusetts Institute of Technology United States Singapore-MIT Alliance for Research & Technology Centre Massachusetts Institute of Technology United States Data Sciences Institute United States Process Chemistry Development Takeda Pharmaceuticals International Company United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore

ISBN: (数字)9781510664548

ISBN: (纸本)9781510664531

We discuss the use of machine learning in computational imaging for manufacturing process inspection and control. In a recent article1 we described a physics-enhanced auto-correlation based estimator (Peace) for quantitative speckle. We derived an explicit forward relationship between the particle size distribution (PSD) and the speckle autocorrelation for particle sizes significantly larger than the wavelength (×100 „ ×1,000). We subsequently trained a machine learning kernel to invert the autocorrelation and obtain the PSD, using the explicit forward model to reduce the number of experimentally acquired examples. In this talk, we present an expanded discussion of Peace and its properties, including spatial and temporal sampling and accuracy, and more general applications. © 2023 SPIE. All rights reserved.

关键词： Autocorrelation

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Historical Review of Hydrogen Energy Storage Technology

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World Journal of engineering and Technology 2023年第3期11卷 454-475页

作者： Wilson Fidelis Ekpotu Joseph Akintola Martins Chineme Obialor Udom Philemon Department of Chemical & Petroleum Engineering University of Uyo Akwa Ibom Nigeria Department of Research & Development Vitapur Nigeria Limited Lagos Nigeria Nubyira Process Designer Abuja Nigeria

Hydrogen energy as a sustainable energy source has most recently become an increasingly important renewable energy resource due to its ability to power fuel cells in zero-emission vehicles and its help in lowering the levels of CO2 emissions. Also, hydrogen has a high energy density and can be utilized in a wide range of applications. It is indeed the fuel of the future but, it is still not entirely apparent how to analyze the most successful ways for hydrogen storage based on technological configuration, nature, and efficiency mechanisms. The historical hydrogen storage technologies as they are presented by the current research have been evaluated, analyzed, and examined in this study. The two categories of hydrogen storage systems are physical-based and *** first category involves storing hydrogen as liquid, cold/cryo-compressed, and compressed gas. Chemical sorption/chemisorption and physical sorption/physisorption are the two primary sub-groups of material-based storage, respectively. The quantitative and qualitative analyses of storage technologies for hydrogen are evaluated in this paper. Also, this report reviews the major safety and reliability issues currently facing hydrogen storage systems. Suggestions are made to assist lay the groundwork for future risk and reliability analysis to ensure safe, dependable operation.

关键词： Hydrogen Energy Energy Storage Sustainable Energy Hydrogen Storage Energy Source

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