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At least 1,549 records · Page 86

Reducing Thermal Degradation of Perovskite Solar Cells during Vacuum Lamination by Internal Diffusion Barriers

Current photovoltaic (PV) panels typically contain interconnected solar cells that are vacuum laminated with a polymer encapsulant between two pieces of glass or glass with a polymer backsheet. This packaging approach is ubiquitous in conventional photovoltaic technologies such as silicon and thinfilm solar modules, contributing to thermal management, mechanical reinforcement, and environmental protection to enable the long lifetimes necessary to become financially acceptable. Commercial vacuum lamination processes typically occur at 150 °C to ensure cross-linking and/or glass bonding of the encapsulant to the glass and PV cells. Perovskite solar cells (PSCs) have emerged as a promising next-generation PV technology that is known to degrade under thermal stresses, especially at temperatures above 100 °C. In this study, we determine degradation modes during lamination and engineer internal diffusion barriers within the PSC to withstand the harsh thermal conditions of vacuum lamination. PSCs with self-assembled monolayers at the ITO interface and SnO X layers deposited by atomic layer deposition at the electron extraction side of the device endured vacuum lamination at conditions typical of commercial PV processes (150 °C) without degradation. This work demonstrates that perovskite PV can be integrated into the existing module lamination process, enabling future single- and multijunction modules utilizing perovskite absorbers.

14 SOLAR ENERGY↗

Eliminating Signal Bias Caused by Vacuum System Backstreaming in the Diagnostic Residual Gas Analyzer of ITER

In fusion neutral gas analysis, such as with the Diagnostic Residual Gas Analyzer (DRGA) for ITER, the primary measurement range of interest comprises the low-amu species (1 to 6), especially deuterium and helium. The challenge in successfully obtaining accurate measurements is two-fold. First, the sensitivity of the method must be sufficient to resolve trace amounts accurately; typically, one percent or less. Second, the gas signal from the fusion processes must be free of bias caused by the latent presence (from system outgassing and/or vacuum backstreaming) of these gases to enable accurate interpretation of the measured signal. This latter criterion can be problematic for the lightest gases since there is a propensity for some fraction of the pumped gas load to undergo a phenomenon known as backstreaming. This behavior is manifested in pumping systems for gas properties related to relative atomic weight (lightest) and size (smallest). Backstreaming results in a significant amount of the pumped gas undertaking a reverse flow and re-entering the measurement region; thus, contaminating the forward, real-time measurement. To fully eliminate this adverse effect, a conductance-limiting device – or orifice – has been installed in the high-vacuum pumping system of the present ITER DRGA prototype. The system was already equipped with a secondary turbomolecular pump (TMP), but with limited effectiveness against backstreaming in the inter-pump volume (IPV). This orifice is placed within the suction inlet coupling of the secondary TMP, which is downstream of the IPV. Its objective is to eliminate the backstreaming phenomenon by increasing the back pressure in the IPV. However, the orifice sizing must take into consideration other factors, such as the diagnostic measurement objectives. For example, in the ITER DRGA, one of the measurement requirements is a dynamic response time of ~1s. Fortunately, an added benefit of the pumping restriction created by the orifice is that the upstream pressure increase is beneficial for the DRGA’s optical gas analysis (OGA) sensors. These sensors are attached to the IPV in the present design. The glow discharges, when used as an OGA light source, will typically have a brighter light emission with increasing plasma cell pressure. In addition to the fusion machine research sector, there are other potential applications of this pumping technique where the monitoring of lighter gas concentrations is essential, such as the photolithography process for the semiconductor fabrication of integrated circuits. This presentation will describe the vacuum system used to demonstrate a process to eliminate backstreaming as well as show test results to verify the accomplishment of this critical objective.

Marcus, Chris↗

Spin-wave based realization of optical computing primitives

We use micromagnetic simulations to demonstrate that spin waves can perform optically inspired, non-Boolean computing algorithms. We propose and design coherent spin-wave sources and phase shifters, which act akin to the key components of an optical signal processing system. We show that the functionality of the proposed on-chip spin-wave based signal processing system is similar to known optical computing devices. We argue that such computing system can serve as a practical, energy efficient, and integrated component of nanoscale image processing systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Algorithmically scalable block preconditioner for fully implicit shallow-water equations in CAM-SE

Performing accurate and efficient numerical simulation of global atmospheric climate models is challenging due to the disparate length and time scales over which physical processes interact. Implicit solvers enable the physical system to be integrated with a time step commensurate with processes being studied. The dominant cost of an implicit time step is the ancillary linear system solves, so we have developed a preconditioner aimed at improving the efficiency of these linear system solves. Our preconditioner is based on an approximate block factorization of the linearized shallow-water equations and has been implemented within the spectral element dynamical core within the Community Atmospheric Model (CAM-SE). Furthermore, in this paper we discuss the development and scalability of the preconditioner for a suite of test cases with the implicit shallow-water solver within CAM-SE.

97 MATHEMATICS AND COMPUTING↗

7th World Congress on Integrated Computational Materials Engineering (ICME 2023) (Final Technical Report)

Integrated Computational Materials Engineering (ICME) has received international attention due to its potential to shorten product development time, while lowering cost and improving design and manufacturing outcomes. ICME is an approach to designing materials solutions for specific applications that use computer modeling programs to predict the behavior of materials and integrate this information into the overall materials, processing, and manufacturing design cycle. The 7th World Congress on Integrated Computational Materials Engineering (ICME 2023) was held in Orlando, Florida from May 21–25, 2023 with the goal to convene stakeholders from across all areas of modeling and simulation, experimental specialization, and design, as well as from across academia, government, and industry, to address ICME tools and techniques and their integration, as well as to examine their application in engineering. This atmosphere facilitated rich interactions between the experimentalists, modelers, and computational and design, from academia, government, and industry, to discuss ICME tools and techniques and their application in engineering.

36 MATERIALS SCIENCE↗

TU-C-18C-01: Medical Physics 1.0 to 2.0: Introduction and Panel Discussion

Medical Physics 2.0, a new frontier in clinical imaging physics: Diagnostic imaging has always been a technological highlight of modern medicine. Imaging systems, with their ever-expanding advancement in terms of technology and application, increasingly require skilled expertise to understand the delicacy of their operation, monitor their performance, design their effective use, and ensure their overall quality and safety, scientifically and in quantitative terms. Physicists can play a crucial role in that process. But that role has largely remained a severely untapped resource. Many imaging centers fail to appreciate this potential, with medical physics groups either nonexistent or highly understaffed and their services poorly integrated into the patient care process. As a field, we have yet to define and enact how the clinical physicist can engage as an active, effective, and integral member of the clinical team, and how the services that she/he provides can be financially accounted for. Physicists do and will always contribute to research and development. However, their indispensible contribution to clinical imaging operations is something that has not been adequately established. That, in conjunction with new realities of healthcare practice, indicates a growing need to establish an updated approach to clinical medical imaging physics. This presentation aims to describe a vision as how clinical imaging physics can expand beyond traditional insular models of inspection and acceptance testing, oriented toward compliance, towards team-based models of operational engagement addressing topics such as new non-classical challenges of new technologies, quantitative imaging, and operational optimization. The Medical Physics 2.0 paradigm extends clinical medical physics from isolated characterization of inherent properties of the equipment to effective use of the equipment and to retrospective evaluation of clinical performance. This is an existential transition of the field that speaks to the new paradigms of value-based and evidence-based medicine, comparative effectiveness, and meaningful use. The panel discussion that follows includes prominent practitioners, thinkers, and leaders that would lead the discussion on how Medical Physics 2.0 can be actualized. Topics of discussion will include the administrative, financial, regulatory, and accreditation requirements of the new paradigm, effective models of practice, and the steps that we need to take to make MP 2.0 a reality. Learning Objectives: To understand the new paradigm of clinical medical physics practice extending from traditional insular models of compliance towards teambased models of operational engagement. To understand how clinical physics can most effectively contribute to clinical care. Learn to identify strengths and weaknesses in studies designed to measure the effect of low doses of ionizing radiation To recognize the impediments to Medical Physics 2.0 paradigm.

60 APPLIED LIFE SCIENCES↗

ProCAFD: Computer-aided Tool for Sustainable Process Synthesis, Intensification and Hybrid solutions

Process industry is always in quest for innovative designs which are both efficient, safe and sustainable. The feasible search space of all unit operations that can be combined to generate process flowsheet alternatives for a given synthesis problem can be large and difficult to manually navigate in order to determine the best processing route. Therefore, it is helpful to utilize computer-aided methods and tools to enumerate, analyze and determine within the design space, the more sustainable processes. In this study, an integrated computer-aided method and corresponding software-tool that’s capable of generating and searching the entire design space for more sustainable process options is presented. In this work a comprehensive analysis method consisting of economic, life cycle, sustainability and process safety indicators is used to identify process bottlenecks on the selected alternative which are translated to design targets. Matching of these design targets minimizes/eliminates the process hot-spots and, thereby generating non-trade-off innovative process designs.

97 MATHEMATICS AND COMPUTING↗

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Abstract To improve the predictive capability of ecosystem biogeochemical models (EBMs), we discuss the feasibility of formulating biogeochemical processes using physical rules that have underpinned the many successes in computational physics and chemistry. We argue that the currently popular empirically based approaches, such as multiplicative empirical response functions and the law of the minimum, will not lead to EBM formulations that can be continuously refined to incorporate improved mechanistic understanding and empirical observations of biogeochemical processes. Instead, we propose that EBM parameterizations, as a lossy data compression problem, can be better formulated using established physical rules widely used in computational physics and chemistry, and different biogeochemical processes can be more robustly integrated within a reactive‐transport framework. Through several examples, we demonstrate how mathematical representations derived from physical rules can improve understanding of relevant biogeochemical processes and enable more effective communication between modelers, observationalists, and experimentalists regarding essential questions, such as what measurements are needed to meaningfully inform models and how can models generate new process‐level hypotheses to test in empirical studies. Finally, while empirical models with more parameters are often less robust, physical rules‐based models can be more robust and show lower predictive equifinality, stemming from their enhanced consistency in representations of processes, interactions and spatial scaling.

54 ENVIRONMENTAL SCIENCES↗

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗

Community Modeling and Long-Term Predictions of the Integrated Water Cycle. Report from the September 2012 Workshop

Water is a key component of the earth and human systems due to its strong interactions with the energy cycle and its vital roles in the energy-water-land system. Uncertainties in predicting the integrated water cycle can limit our abilities to address the energy and environmental challenges today and in the future. Modeling the integrated water cycle contributes to the Department of Energy’s (DOE) core competencies in integrative modeling, drawing from unique and highly relevant research on cloud, aerosol, terrestrial ecosystem, carbon cycle, and subsurface processes, as well as climate and earth system modeling and integrated assessment modeling. Synthesizing new process knowledge and innovative computational methods in integrated models of the human-earth system can advance predictive capabilities relevant to DOE missions. This report describes the DOE workshop on Community Modeling and Long-Term Predictions of the Integrated Water Cycle, held September 2012 in Washington DC. The workshop serves as a launching point and major organizing event to identify challenges and plan the development of next-generation human-earth system models for improving long-term predictions of the regional-scale integrated water cycle. More specifically, the workshop aims to: identify core modeling capabilities while identifying key research gaps, with an emphasis on improving model fidelity; reveal relevant and critical capabilities and needs for observations, analytical frameworks, and data management that underpin the development, testing, and validation of our main models and model components; engage the research community in strategies for improving synthesis and integration; elucidate opportunities for collaborations within DOE and with other agencies and institutions that have complementary and essential expertise in specific aspects of the water cycle; and improve understanding of the nature and characteristics of long-term scientific information requirements for DOE’s energy and environmental missions and, as appropriate, for mission needs of other partner agencies. The workshop benefited from substantial inputs provided by the broad scientific community and interagency participation. The topical and crosscutting research challenges identified at the workshop have been synthesized into three overarching Science Grand Challenges and three Integrative Modeling Experiments summarized in this report. These challenges represent remarkable opportunities for interagency collaborations to improve predictions of the integrated water cycle for significant scientific and user impacts.

54 ENVIRONMENTAL SCIENCES↗

A U.S. Scientific Community Vision for Sustained Earth Observations of Greenhouse Gases to Support Local to Global Action

Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top‐down/bottom‐up analyses to link process understanding to global assessment.

Parazoo, Nicholas C. [California Institute of Tech↗

TXM-Sandbox : an open-source software for transmission X-ray microscopy data analysis

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook . Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

36 MATERIALS SCIENCE↗

NREL's Capabilities in Techno-Economic and Sustainability Analyses for Thermal and Catalytic Conversion of Biomass and Waste Feedstocks

The Thermal and Catalytic Process Development Unit at NREL has state-of-the-art equipment for thermochemical process development and testing, ranging from catalyst and feedstock characterizations to bench-scale reactors to pilot plants. Within this facility is the capability to integrate experimental results with detailed process models to estimate biomass conversion costs. This fact sheet summarizes the core capabilities and applications.

09 BIOMASS FUELS↗

Electrically-Assisted Tubing Processes for Enhancing Manufacturability of Oxide Dispersion Strengthened Structural Materials for Nuclear Reactor Applications

The overall goal of this project is to enhance the formability of Nanostructured Ferritic Alloys (NFAs) such that high-strength thin-walled claddings can be successfully and economically manufactured for use in future nuclear reactors. Specifically, four objectives were identified: Objective #1 – to achieve a good understanding of the mechanical behavior and resulting microstructure of 14YWT made from the powder form subjected to various Electrically- Assisted (EA) loading conditions. Objective #2 – to conduct EA-flat rolling of 14YWT completed and the prioritization/selection of two alternative designs of EA tube rolling processes. Objective #3 – to design and assemble a new EA tube rolling machine. Objective #4 – to conduct rolling using the new EA rolling machine. The above objectives were achieved and the findings can be further applied to establish other innovative fabrication processes. Specifically, the major accomplishments are summarized as: The use of an EA forming process was investigated to reduce the forming force of ODS ferritic steels. The effect of a continuous electric current on 14YWT during plastic deformation was evaluated. EA uniaxial tension tests show that the electric current is able to reduce the flow stress of 14YWT. 14YWT exhibits a ductility minimum at a current density of 34.5 A/mm2 which is consistent with fractography results. Hardness measurements and TEM results indicate that oxide particles are stable during the EA process. By following the tests, microstructure analysis was performed on the sample in its as-received state and after current treatment. The microstructures are stable when subjected to high current density. The related thermal model was developed to predict the Joule heating temperatures. The temperatures were compared with the experimental results. At last, a temperature-dependent hardening model was used to explore the mechanisms acting during EA deformation. Since the model can accurately predict the yield strength of 14YWT under EA conditions without the incorporation of non-thermal effects, it can be concluded that the reduction in yield strength is due to the Joule heating generated under continuous current loading conditions. An oven-heated pure thermal tension test was conducted to confirm this conclusion. The new EA tube rolling machine has been completely developed. The related work includes: (1) forming process design; (2) analysis of the effect of roll-tube contact geometry on rolling force; (3) analysis of machine performance under mechanical loading; (4) design of machine electrical setting path and insulation; (5) multi-pass process analysis; (6) design of power transmission system (axial/radial/torque feeding mechanisms), roll bearing system, cooling system, workpiece feeding mechanism, and other related mechanical connection support components; (7) design and optimization of roll profiles/dimensions; (8) analysis and simulation of the rolling process; (9) development of engineering drawings and fabrication; (10) assembly and calibration of the EA tube rolling machine; (11) design and integration of the electrical control system; (12) hardware integration for high power supply electrically-assisted rolling process; (13) induction heating system integration; (14) experimental tests for the new rolling process. Through the process from conceptual design to final machine calibration and experimental tests, there are many technical and physical works that have been implemented and improved for the best performance of the innovative prototype.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Regional Nature of Global Challenges. A Need and Strategy for Integrated Regional Modeling

In this paper, we explore the regional nature of global environmental challenges. We take a broad approach by examining the scientific foundation that is needed to support policy and decision making and identifying some of the most important barriers to progress that are truly scale-dependent. In so doing, we hope to show that understanding global environmental changes requires understanding a number of intrinsically regional phenomena, and that successful decision making likewise requires an integrated approach that accounts for a variety of regional Earth system processes—which we define to include both human activities and environmental systems that operate or interact primarily at sub-continental scales. Understanding regional processes and phenomena, including regional decision-making processes and information needs, should thus be an integral part of the global change research agenda. To address some of the key issues and challenges, we propose an integrated regional modeling approach that accounts for the dynamic interactions among physical, ecological, biogeochemical, and human processes and provides relevant information to regional decision makers and stakeholders.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of Hydrogen Production Feasibility for a Light Water Reactor in the Midwest

Increased electricity production from renewable energy resources coupled with low natural gas prices has caused existing light-water reactor (LWRs) to experience ever diminishing returns from the electricity market. Via partnership among Idaho National Laboratory (INL), The National Renewable Energy Laboratory (NREL), Argonne National Laboratory (ANL), Exelon, and Fuel Cell Energy a techno-economic analysis on the viability of retrofitting existing pressurized water reactors (PWRs) to produce hydrogen (H2) via high temperature steam electrolysis (HTSE) has been conducted. Such integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long-term. To accommodate such an integration, a detailed analysis of HTSE process operation, requirements, and flexibility was conducted. Technical analysis includes proposed nuclear system control scheme modifications to allow dynamic operation of the HTSE via both thermal and electrical connection to the nuclear plant. High fidelity Modelica simulations showcase the viability of such control schemes. However, due to limited knowledge of solid oxide fuel cell (SOFC) stack degradation due to thermal gradients; thermal cycling of the HTSE was not included. Therefore, the control schemes proposed are only utilized to re-distribute steam at startup and only the portion of electricity utilized in the electrolyzers is cycled. From the detailed analysis of the nuclear integration and the HTSE process design, a comprehensive cost estimation was conducted in the APEA and H2A models to elucidate capital and operational costs associated with the production, compression, and distribution of hydrogen from a nuclear facility. Alongside this costing analysis, market analyses were conducted by NREL and ANL on the electric and hydrogen markets respectively in the PJM interconnect. Utilizing the electricity data market projections in the PJM interconnect from NREL and hydrogen demand/pricing projections from ANL a five variable sweep over component capacities, discount rates, and hydrogen pricing was completed using the stochastic framework RAVEN (Risk Analysis Virtual ENVironment) through its resource dispatch plugin HERON (Heuristic Energy Resource Optimization Network). Each combination of variables was evaluated stochastically four times over a seventeen year timespan from 2026-2042 (inclusive) to determine the most economically advantageous solution. Following the five variable sweep an optimization was conducted about the best sweep point to determine optimal component sizing and setpoints. Results suggest positive gain is achievable at all projected hydrogen market pricing levels and at all discount rates. However, exact component sizing and net returns vary based on these values and if incorrect sizing is selected; major net losses can occur. The optimal result occurred with set points as follows: high hydrogen prices, the largest possible HTSE unit in the sweep set at 7.47 kg/sec [645.4 tpd], a contractual hydrogen market agreement 7.29 kg/sec [629.8 tpd], and a hydrogen storage size 115,188 kg. The analysis suggested that with a discount rate of 8%, a ΔNPV = 1.2 billion over the seventeen year span can be achieved. The results illuminate that by operating in multiple markets the nuclear facility is capable of avoiding sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted in this report is a differential cash flow analysis and as such does not present profit levels. Instead it highlights the net benefit between building and competing in the hydrogen market utilizing nuclear facilities and conducting business as usual in the electricity markets. Additionally, results presented in this report exhibit conservatism due to four key assumptions: Given the limited knowledge on SOFC stack degradation due to thermal gradients the high temperature steam electrolysis plant is not allowed to thermally cycle. This limitation decreases electricity generation capacity in the nuclear plant, reducing capacity payments and the maximum output to the electrical grid. This analysis considers building a separate hydrogen pipeline for use in the nuclear facility. Research is currently being conducted to determine if existing natural gas pipelines can accommodate direct hydrogen injection. If hydrogen can be integrated into existing natural gas pipelines then a capital savings of ~$19,000,000 per kg/sec [1 kg/sec = 86.4 tpd] of installed HTSE capacity could be realized. Fast transients in the electric grid are typically served by flywheels and electric batteries. With electrolysis only operation the nuclear plant can flex its electricity just as quickly. However, for this analysis, the ancillary services market has been neglected. Should the nuclear plant have the ability to operate in the ancillary services market during periods when it is producing hydrogen, an additional substantial income stream that would increase overall system profitability could be considered. Subsidies for non-emitting generation technologies are not introduced in the cash flow analysis, but instead are completed assuming zero subsidies. Profitability is based solely on electricity pricing. Electric pricing is assumed to never go negative. Instead, it is assumed overall system curtailment by the Independent System Operator (ISO) will occur in such a manner that pricing remains at or above zero. This assumption inflates the “business as usual” scenario, thus decreasing the ΔNPV calculated. If negative pricing scenarios continue to occur as they do today, one would expect a further increase in ΔNPV. Overall, results advocate that, through market diversification, nuclear power plants have the potential to substantially increase current profit margins, increase market penetration, and ultimately solidify their place as a mainstay in energy production.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Towards 5G-Enabled Operational Technology for Process Monitoring and Network Slicing

Cyber-Physical Systems (CPS) are deployed to monitor physical processes in critical cyber-enabled services like power generation. However, CPS ecosystems are typically designed without robust security. While it is important to ensure optimal performance of the Operational Technology (OT) environments, security cannot be overlooked. To modernize traditional OT services, 5G technology is being integrated. 5G technology offers low latency and high availability, making it a suitable infrastructure for managing and monitoring physical processes. How-ever, integrating 5G mechanisms into large-scale OT networks introduces new implementation and performance challenges. Therefore, this paper presents a 5G-enabled CPS architecture (5G-CPS) that describes the necessary components, services, and communication protocols and conducts feasibility study to integrate 5G technology in industrial control system networks to understand the performance merits. The 5G-CPS architecture aims to minimize implementation and operational challenges associated with integrating 5G technology into constrained OT.

Aguayo, Jared M.↗

Accelerator Integration in CMS [Slides]

CMS data processing framework uses a mechanism to interact effectively with non-cpu resources. Non-CPU algorithms are divided into 3 phases: (1) CPU stage which acquires data and transfers to non-CPU resource, (2) Non-CPU algorithm is then run, and (3) When finished, a publish step is run on the CPU to move data back to CPU memory. While non-CPU algorithm runs, the CPU is available for other algorithms.

97 MATHEMATICS AND COMPUTING↗