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At least 811 records · Page 45

Improving the Accuracy of Quadrature Method Solutions of Fredholm Integral Equations That Arise from Nonlinear Two-Point Boundary Value Problems

In this paper we are concerned with high-accuracy quadrature method solutions of nonlinear Fredholm integral equations of the form y(x) = r(x) + definite integral of g(x, t)F(t,y(t))dt with limits between 0 and 1,0 less than or equal to x les than or equal to 1, where the kernel function g(x,t) is continuous, but its partial derivatives have finite jump discontinuities across x = t. Such integral equations arise, e.g., when one applied Green's function techniques to nonlinear two-point boundary value problems of the form y "(x) =f(x,y(x)), 0 less than or equal to x less than or equal to 1, with y(0) = y(sub 0) and y(l) = y(sub l), or other linear boundary conditions. A quadrature method that is especially suitable and that has been employed for such equations is one based on the trepezoidal rule that has a low accuracy. By analyzing the corresponding Euler-Maclaurin expansion, we derive suitable correction terms that we add to the trapezoidal rule, thus obtaining new numerical quadrature formulas of arbitrarily high accuracy that we also use in defining quadrature methods for the integral equations above. We prove an existence and uniqueness theorem for the quadrature method solutions, and show that their accuracy is the same as that of the underlying quadrature formula. The solution of the nonlinear systems resulting from the quadrature methods is achieved through successive approximations whose convergence is also proved. The results are demonstrated with numerical examples.

Sidi, Avram↗

Integrating Analytical Solutions and U-Net Model for Predicting Groundwater Contaminant Plumes in Pump-and-Treat Systems

Pump-and-treat (P&T) is a common technique for groundwater remediation involving the extraction and treatment of contaminated water above ground. Optimizing the design and operation of the P&T well network is essential for maximizing the system’s effectiveness and efficiency. However, this optimization often necessitates many model evaluations, leading to computationally demanding tasks. This study introduces a novel approach that integrates analytical solutions for groundwater dynamics with the U-Net (Ronneberger et al., 2015) deep learning framework to predict groundwater contaminant plume migration under dynamic pumping conditions. By incorporating the Thiem equation (Thiem, 1906) into the input preprocessing, the U-Net model transforms sparse well data into a continuous spatial field that captures the hydraulic impacts of pumping activities. This integration enables the model to leverage both deep learning capabilities and classical physics-based groundwater theories, enhancing prediction accuracy and computational efficiency. These advancements can facilitate rapid, large-scale evaluations of P&T optimization simulations, allowing for timely and effective decision-making in well placement and system management. We demonstrate the model's robust performance across both simplified transient 2D models and a more complex 3D heterogeneous site model at the 200 West P&T facility at the Hanford Site. The U-Net-based model offers substantial computational advantages, reducing simulation times significantly compared to full physics-based models and providing a powerful tool for rapid site evaluation and P&T system optimization, such as evaluating alternative P&T well network designs. Our findings highlight the potential of advanced machine learning models to significantly enhance the efficiency and sustainability of groundwater remediation efforts, offering a novel application of U-Net architecture in environmental science.

Pump-and-treat↗

Impact of FERC Order 2222 on DER Participation Rules in US Electricity Markets

Electricity markets in the bulk grid are beginning to implement market mechanisms that support the procurement of flexible capabilities from wide range of technologies, including distributed energy resources (DERs). The flexibility of these resources will help counterbalance supply uncertainties from large-scale integration of variable renewable generation. To encourage development of distributed and aggregated market participants, FERC Order 2222 was issued in September 2020 to require each Independent System Operator (ISO) in the US to implement rules that enable broader participation from aggregations of DERs in the bulk market. The following paper first describes the generic design of ISO markets before introducing the new market participation rules that ISOs have proposed for compliance with Order 2222. The paper then describes how software performance issues may continue to affect the eligibility requirements and offer structures for DER aggregations participating in ISOs, noting that continued research on computational methods may help reduce burdens for DER integration. The prospects for transmission and distribution system coordination is second major issue discussed, which will require minor changes to existing processes in the short term. In the longer term, there is more opportunity for more wide-ranging reforms, such as the development of a Distribution System Operator (DSO) framework. Newly proposed market rules may affect how Transactive Energy Systems (TES) will help facilitate efficient formation of DER aggregations and operation of the individual DERs within an aggregation. Within the TES context, the challenge is to fully understand how resource eligibility and operational and planning coordination methods will affect the design and implementation of TES.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Pressure Shell Approach to Integrated Environmental Protection

The next generation of exploration mission human systems will require environmental protection such as radiation protection that is effective and efficient. In order to continue human exploration, habitat systems will require special shells to protect astronauts from hostile environments. The Pressure Shell Approach to integrated environmental (radiation) protection is a multi-layer shell that can be used for multifunctional environmental protection. Self-healing, self-repairing nano technologies and sensors are incorporated into the shell. This shell consists of multiple layers that can be tailored for specific environmental protection needs. Mainly, this innovation focuses on protecting crew from exposure to micrometeorites, thermal, solar flares, and galactic cosmic ray (GCR) radiation. The Pressure Shell Approach consists of a micrometeoroid and secondary ejecta protection layer; a thin, composite shell placed in between two layers that is non-structural; an open cavity layer that can be filled with water, regolith, or polyethylene foam; a thicker composite shell that is a structural load bearing that is placed between two layers; and a bladder coating on the interior composite shell. This multi-layer shell creates an effective radiation protection system. Most of its layers can be designed with the materials necessary for specific environments. In situ materials such as water or regolith can be added to the shell design for supplemental radiation protection.

Kennedy, Kriss J.↗

Packet Controller For Wireless Headset

Packet-message controller implements communications protocol of network of wireless headsets. Designed for headset application, readily adapted to other uses; slight modification enables controller to implement Integrated Services Digital Network (ISDN) X.25 protocol, giving far-reaching applications in telecommunications. Circuit converts continuous voice signals into digital packets of data and vice versa. Operates in master or slave mode. Controller reduced to single complementary metal oxide/semiconductor integrated-circuit chip. Occupies minimal space in headset and consumes little power, extending life of headset battery.

Christensen, Kurt K.↗

High Temperature Optocoupler for 3D High Density Power Modules

The goal of this proposed research is to develop a reliable high-temperature optocouplers, which can operate at 250°C with at least ten-year lifetime, and replace isolation transforms as the galvanic isolation solution for the 3D integration of high density power modules. The electrification of future transportations (i.e., electric vehicles) will continuously drive the demand for high density power modules. Optocouplers (i.e., packaged light emitter and detector) as a promising candidate to replace bulky isolation transformers are highly desirable to facilitate the continuous scale-down of gate driver circuitry that will lead to 3D high density power modules and achieve disruptive performance in terms of thermal management, power density, power efficiency, reliability and operating environments. However, regular semiconductor optoelectronic materials and devices have significant difficulty functioning in the harsh environments designated for high density power module usage (such as operation at high temperatures). Ultimately, it is not the intrinsic properties of power devices that prevent their use at higher temperatures, but rather the low voltage electronics needed to drive them and the packaging that surrounds them. The typical operating temperature for optocouplers is only up to 100°C, due to the limitations of light emitting diode (LED) devices inside and packaging materials. A systematic characterization methodology will be developed to analyze the performance, lifetime and reliability of LED devices and distinguish multiple failure mechanisms at high temperatures. An original methodology of “design for reliability” will be developed to design the optoelectronic devices with high reliability and long lifetime at high temperatures. A new architecture of high temperature high reliable optocouplers will be developed, fabricated and demonstrated with continuous operating at 250°C. The development of efficient, reliable high density 3D power modules is the foundation for energy efficiency and energy reliability. Enabled with advanced 3D integration and packaging technologies, high density power module solutions can achieve much more superior performance over the conventional discrete solutions in terms of efficiency, thermal management and power density. The proposed concept of high temperature optocouplers as the galvanic isolation solution for high density power modules will bring together interdisciplinary research involving the wide bandgap materials, optoelectronics, high reliable device design, electronics packaging and power modules. A streamline of skilled personnel would be trained including graduate and undergraduate students, local engineers and scientists which are in great demand to both academia and optoelectronics industry. The proposed research topics, such as, solid state lighting and high temperature device reliability, are currently of major interest at the Department of Energy, in particular, Sandia National Laboratories. This project can enhance collaborations between the University of Arkansas (UA) and Sandia National Laboratories. The findings of the proposed research are expected to be integrated into high density 3-D power modules at the Engineering Research Center for Power Optimization for Electro-Thermal Systems (POETS).

42 ENGINEERING↗

Recent advances in CO2 laser catalysts

This paper discusses several recent advances in CO2 laser catalysts including comparisons of the activity of Au/MnO2 to Pt/SnO2 catalysts with possible explanations for observed differences. The catalysts are compared for the effect of test gas composition, pretreatment temperature, isotopic integrity, long term activity, and gold loading effects on the Au/MnO2 catalyst activity. Tests conducted to date include both long-term tests of up to six months continuous operation and short-term tests of one week or more that include isotopic integrity testing.

Upchurch, B. T.↗

Scale-Up of the Carbon Dioxide Removal by Ionic Liquid Sorbent (CDRILS) System

The Carbon Dioxide Removal by Ionic Liquid Sorbent (CDRILS) system is designed for efficient, safe and reliable carbon dioxide (CO2) removal from cabin air on long-duration missions to the Moon, deep space, and Mars. CDRILS integrates an ionic liquid sorbent with hollow fiber membrane contactors for rapid CO2 removal and recovery. The liquid-based system provides continuous CO2 delivery, which avoids complicated valve networks to switch between absorbing and desorbing beds and enables simpler integration to the Sabatier without the need for the CO2 Management System (CMS). Ionic liquids are particularly desirable as liquid absorbents for space applications since they are non-volatile, non-odorous, and have high oxidative stability. The hollow fiber membrane contactors offer both high contact area and rigorous containment between the gas and liquid phases in a microgravity environment. Scale-up of the CDRILS technology has presented a series of fascinating challenges, since the interaction between hollow fiber properties, ionic liquid properties and performance is complex. Properties measured with lab-scale hollow fiber contactors are used to estimate the performance of contactors that are similar in scale to flight-scale demonstrations. To accomplish this, component and system models have been built to relate the key scrubber and stripper design and operating variables with performance, and experiments directed to validate the models have been performed. System size, weight and power are determined by component selection, arrangement, and operating conditions. Reliability will be extremely important for any long-range mission and depends on the stability of the ionic liquids and hollow fiber contactors. We report on our continuing long term stability experiments for the ionic liquid and contactor materials and our investigation of the physical properties of additional ionic liquids.

Yates, Stephen F.↗

Demonstration of the Human and Technology Integration Guidance for the Design of Plant-Specific Advanced Automation and Data Visualization Techniques

Nuclear power continues to be a safe, reliable, and carbon-free electricity generating source for the United States, though the cost of operating and maintaining the current United States nuclear power plant fleet has become uncompetitive with other sources. This gap is attributed to the advent of new digital instrumentation and control technologies that other electricity generating industries are currently leveraging to streamline work and greatly reduce operating, maintenance, and support costs. Digital instrumentation and control systems and control room modernization offers significant opportunities to reduce operating and maintenance costs to ensure the continued operation of the existing United States light-water reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Solid state thermostat has integral probe and circuitry

Compact, reliable thermostat provides a temperature readout signal and a continuous temperature-control output for temperature monitoring by automatic checkout equipment or telemetry systems. It employs a solid state circuit in a housing rigidly attached to a thermistor probe.

Source record↗

Integrated electrochemical nuclear decontamination system

An electrochemical cell that oxidizes a solution provides a continuous and stable supply of an oxidizing ion solution to a fixture or vessel used for the purposes of decontaminating metal and metal alloys. The electrochemical cell includes an anode compartment that oxidizes the solution in nitric acid or methane sulfonic acid at a rate equal to or greater than a rate of reduction, or generates the oxidizing ions prior to use in a batch. The electrochemical cell is part of a larger system that facilitates online measurement system which measures the oxidizing ion solution and the dissolved PuO 2 , UO 2 , AmO 2 , other radionuclides, or other contaminates in real-time. Solution decontamination system removes the dissolved PuO 2 /UO 2 /AmO 2 , other radionuclides, or other contaminates from the oxidizing ion solution, real time acoustic monitoring of the thickness of the surface being contaminated, and automation of a delivery system facilitates flow between surface and electrochemical cell.

Karmiol, Benjamin↗

Enabling energy‐efficient manufacturing of pharmaceutical solid oral dosage forms via integrated techno‐economic analysis and advanced process modeling

Abstract The global pharmaceutical industry is a trillion‐dollar market. However, the pharmaceutical sector often lags in manufacturing innovation and automation which limits its potential to maximize energy efficiency. The integration of techno‐economic analysis (TEA) with advanced process models as part of an overarching smart manufacturing platform, can help industries create business models, which can be adapted for manufacturing to reduce energy consumption and operating costs while ensuring product quality which can further enable a more sustainable process operation. In this study, a rational design of experiment on three unit‐operations (wet granulation, drying, and milling) was performed on a batch (case 1) and continuous (case 2) pharmaceutical process to obtain experimental data. Process models for predicting product quality and energy efficiency of each of the three‐unit operations were developed. The experimental data were used to validate the models and good agreement was observed. The energy consumption of each unit operation was calculated using statistical models relating the power consumption and the process parameters. The developed process models and energy models were further integrated into a TEA framework, which quantified the energy and monetary cost of manufacturing for both batch and continuous manufacturing cases. With this integrated framework, energy costs savings of ~33% was obtained in the continuous manufacturing process (case 2) over the batch process (case 1).

Sampat, Chaitanya↗

Rotordynamic Instability Problems in High-Performance Turbomachinery, 1993

The first rotordynamics workshop proceedings (NASA CP-2133, 1980) emphasized a feeling of uncertainty in predicting the stability of characteristics of high-performance turbomachinery. In the second workshop proceedings (NASA CP-2250, 1982) these uncertainties were reduced through programs established to systematically resolve problems, with emphasis on experimental validation of the forces that influence rotordynamics. In the third proceedings (NASA CP-2338, 1984) many programs for predicting or measuring forces and force coefficients in high-performance turbomachinery produced results. Data became available for designing new machines with enhanced stability characteristics or for upgrading existing machines. In the fourth proceedings (NASA CP-2443, 1986) there emerged trends toward a more unified view of rotordynamic instability problems and several encouraging new analytical developments. The fifth workshop (NASA CP-3026, 1988) supported the continuing trend toward a unified view with several new developments in the design and manufacture of new turbomachineries with enhanced stability characteristics along with new data and associated numerical/theoretical results. The sixth workshop report (NASA CP-3 I 22, 1990) field experience and experimental results, and expanded the use of computational and control techniques with integration of damper, bearing, and eccentric seal operation results. The present workshop continues to report field experiences, numerical, theoretical, and experimental results and control methods for seals, bearings, and dampers with some attention given to variable thermo physical properties and turbulence measurements, and introduction of two-phase flow results. The intent of the workshop and this proceedings is to provide a continuing impetus for an understanding and resolution of these problems.

Instabilities↗

Explorations of Quantum-Classical Approaches to Scheduling a Mars Lander Activity Problem

An effective approach to solving problems involving mixed (continuous and discrete) variables and constraints, such as hybrid systems, is to decompose them into subproblems and integrate dedicated solvers geared toward those subproblems. Here, we introduce a new framework based on a tree search algorithm to solve hybrid discrete-continuous problems that incorporates: (1) a quantum annealer that samples from the configuration space for the discrete portion and provides information about the quality of the samples, and (2) a classical computer that makes use of information from the quantum annealer to prune and focus the search as well as check a continuous constraint. We consider four variants of our algorithm, each with progressively more guidance from the results provided by the quantum annealer. We empirically test our algorithm and compare the variants on a simplified Mars Lander task scheduling problem. Variants with more guidance from the quantum annealer have better performance.

scheduling↗

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗

Physics-informed machine learning

Despite great progress in simulating multiphysics problems using the numerical discretization of partial differential equations (PDEs), one still cannot seamlessly incorporate noisy data into existing algorithms, mesh generation remains complex, and high-dimensional problems governed by parameterized PDEs cannot be tackled. Moreover, solving inverse problems with hidden physics is often prohibitively expensive and requires different formulations and elaborate computer codes. Machine learning has emerged as a promising alternative, but training deep neural networks requires big data, not always available for scientific problems. Instead, such networks can be trained from additional information obtained by enforcing the physical laws (for example, at random points in the continuous space-time domain). Such physics-informed learning integrates (noisy) data and mathematical models, and implements them through neural networks or other kernel-based regression networks. Moreover, it may be possible to design specialized network architectures that automatically satisfy some of the physical invariants for better accuracy, faster training and improved generalization. Furthermore, we review some of the prevailing trends in embedding physics into machine learning, present some of the current capabilities and limitations and discuss diverse applications of physics-informed learning both for forward and inverse problems, including discovering hidden physics and tackling high-dimensional problems.

97 MATHEMATICS AND COMPUTING↗

Development of a direct-sampling RF receiver for precision beam charge measurements in the MOLLER experiment

Here, we have developed and tested a direct-sampling RF receiver capable of measuring the amplitude of a 1497 MHz sinusoidal beam signal in 0.5 ms integration windows with a relative uncertainty of better than 10 parts per million. The receiver is intended for measuring signals from beam current monitoring cavities on the beamline of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The beam signal strength, frequency, and integration window fulfill the thus far unmet requirements of the upcoming MOLLER experiment to measure the beam charge for different helicity states.

47 OTHER INSTRUMENTATION↗

A dendritic strontium river isoscape for fisheries applications in the Sacramento River basin, California, USA

Objective Understanding the origins and movements of fish is fundamental to effective conservation and fisheries management. Strontium isotope ratios ( 87 Sr/ 86 Sr) in otoliths provide a powerful tracer of natal origin and migratory pathways. However, existing 87 Sr/ 86 Sr isoscapes for the Sacramento River basin, an ecosystem that supports ecologically and economically important salmon populations, rely on discrete classification approaches that overlook unsampled habitats and do not incorporate spatial uncertainty. Our objective was to develop a continuous, network-explicit 87 Sr/ 86 Sr isoscape with quantified uncertainty to fill in data gaps and enable probabilistic assignments of fish origin and movement. Methods We used river water 87 Sr/ 86 Sr data from 106 sites (1997–2021) to develop spatial stream network models that use dendritic connectivity and watershed characteristics (lithology, bedrock age, and land cover) to predict river water 87 Sr/ 86 Sr throughout the basin. Models were fitted using maximum and restricted likelihood and were evaluated via Akaike’s information criterion and leave-one-out cross validation. We produced both historical (pre-dam) and present-day (below-dam) isoscapes, delineated uncertainty-informed isotopic ranges using k -means clustering, and applied a proof-of-concept Bayesian assignment to estimate natal origins and early rearing habitats for two endangered winter-run Chinook Salmon Oncorhynchus tshawytscha. Results Cross validation indicated strong performance of the 87 Sr/ 86 Sr model (leave-one-out cross validation: R 2 = 0.91; root mean square error = 0.0005). Uncertainty-informed clustering identified 19 isotopic “suites” (reaches with indistinguishable 87 Sr/ 86 Sr values) in present-day anadromous habitats and 25 suites in the historical network. Example natal and early rearing assignments included predictions that challenged expectations for juvenile salmon migration based on predicted river 87 Sr/ 86 Sr compositions. Conclusions This study developed a continuous, network-explicit 87 Sr/ 86 Sr isoscape that integrates existing river data to predict 87 Sr/ 86 Sr in unsampled reaches and the likely achievable range and resolution of otolith-based origin and life history inference. The resulting river isoscape provides a valuable tool to predict salmon movements and identify habitats supporting their survival and growth that otherwise might remain undetected. Coupling these predictions with complementary approaches that ground-truth juvenile presence (e.g., targeted fish surveys) represents an important step toward science-informed restoration and management of critical habitats throughout the Sacramento River basin.

Environmental sciences↗