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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems: Preprint

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2017

Integrating human factors issues into critical portable detection usage - 121

There are multiple situations where portable detection systems are used to quantify distributed radionuclides. Such applications include holdup measurements in decommissioning activities, other routine usage and safeguards applications. Human factors dominate equipment deployment and operation and have significant impact upon the resulting data collection and its quality. Equipment use includes simultaneous positioning and targeting the object/region being quantified, observation and reporting of incoming data, often in difficult conditions and often while dressed in protective equipment. We examine the human interface with the equipment and other human factors where balance, perception, situational awareness and personnel health level influence the physical control and positioning of the detector. All these aspects impact both the measurement outcome and the Total Measurement Uncertainty (TMU). In this work, we are developing approaches and solutions to: 1. Initiate an inclusive program to assess and evolve human factors aspects of the interface to provide real time feedback tailored to a specific field operator profile. 2. Develop a measurement system human interface on a 'bench top' detection system to allow for both audio and visual I/O for auditory attention and situational (objective and subjective) awareness across varied end user characteristics. 3. Assess and develop an enhanced health assessment plan to identify and monitor pertinent auditory and balance characteristics for operator(s) interface and physical control of the gamma detector. Use the plan to verify personnel ability for effective deployment. We take a multidisciplinary approach to maximize accuracy, efficiency, and safety for the end-user to optimize project and measurement performance. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Impact of Heat Dissipation Profiles on Power Electronics Packaging Design

This work focuses on understanding the thermal impacts of using discrete power devices and limitations of applying conventional thermal design methods. Empirically, a thermal system is designed based on selecting a heat sink with the required thermal resistance from the manufacturer datasheet. This method, as an approximate estimation, has been proven effective as a rough design of Si-based power module. However, wide bandgap (WBG) bare dies bring additional thermal design concerns that have been overlooked. The benefits of WBG devices, such as smaller chip sizes and higher power ratings, on the other hand, lead to thermal concentration issues. Detailed analyses and impacts of the thermal concentration are presented in this paper. Finally, a more accurate model involving Finite Element Analysis (FEA) and Genetic Algorithm optimization is also proposed for a more accurate thermal design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Heat transfer model for moving packed-bed particle-to-sCO 2 heat exchangers integrated with metal foams

Particle-to-supercritical carbon dioxide (sCO 2 ) heat exchangers (HXs) play a vital role in coupling heat transfer fluid (HTF) from high-temperature thermal receivers to power cycle working fluids (WF). Heat transfer enhancement is essential for adopting particle-based moving packed-bed heat exchangers (MPBHXs) in next-generation thermal energy storage (TES) systems, as MPBHXs usually exhibit low particle bed-to-wall heat transfer coefficients. High-porosity metal foams have shown their effectiveness in heat transfer enhancement. Here, this work presents a continuum heat transfer model to demonstrate the heat transfer enhancement in MPBHXs when the particle bed channel is filled with high porosity metal foams compared to open channel MPBHXs. The presence of metal foams increases the effective thermal conductivity in the particle channel and enhances the interstitial heat transfer coefficient between the moving particle bed and the stationary metal foams. The present model considers coupled two-dimensional (2D) heat transfer in the particle channel with metal foams and 1D heat transfer in the sCO 2 channel and the dividing wall. The temperature profiles for the particle bed, metal foam, dividing wall, and sCO 2 stream, as well as the local heat flux profiles between those, are studied in detail for various foam porosities, from which the particle bed-to-wall heat transfer coefficient, overall heat transfer coefficient, and total heat transfer rate for the MPBHX are determined. The effects of major MPBHX design and operating parameters on the particle bed-to-wall heat transfer coefficient and overall heat exchange capacity are thoroughly examined; thus, the MPBHX performance improvement with metal foams is quantified for each case. The present heat transfer model can provide valuable insights into the metal-foam MPBHX design and optimization, scale-up, and operating parameters selection.

42 ENGINEERING↗
DOE OSTI2023

Systematically derived thermodynamic properties for alkane oxidation

Key combustion properties, such as ignition delay time, show strong sensitivity to the thermochemistry of the main species in the standard radical oxidation pathway at low temperatures (600-1000K). Significant uncertainties persist in current estimates of thermodynamic properties, particularly for the larger species of relevance to common practical fuels. In this article, we use advanced computational schemes to evaluate thermodynamic properties for the fuel, fuel radical, peroxy, hydroperoxy-alkyl radical, and hydroperoxide species for a set of 17 fuels containing up to 9 carbon atoms, and with various degrees of branching in the alkane backbone. The procedure, termed STAR-1D, combines conformer sampling to find the minimum geometry, B2PLYP-D3/cc-pVTZ harmonic frequency evaluations, and omega B97X-D/cc-pVTZ one-dimensional torsional mapping. It includes two physically-based scaling routines: a frequency-dependent scaling to B2PLYP-D3/cc-pVTZ anharmonic frequencies and a scaling of one-dimensional omega B97X-D/ccpVTZ torsional profiles to reproduce the product of the B2PLYP-D3/cc-pVTZ frequencies in the harmonic limit. Substantive comparisons with existing experimental databases, together with careful examinations of key theoretical assumptions, are used to explore the accuracy of the predictions. These computationally intensive explorations of 195 species were facilitated by automated thermochemistry software. Further, high accuracy 0 K heats of formation from a separate study are used with the STAR-1D computations to generate NASA polynomial representations. In addition to their intrinsic value, the present results also provide a reliable database for the optimization of group additivity or machine learning schemes for scaling to larger combustion systems. Towards this end a complementary extensive conformational analysis is carried out for the medium sized species and the thermodynamic properties of the lowest energy hydrogen-bonded and non-hydrogen bonded conformers are contrasted for larger hydroperoxy-alkyl radical species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Empowering multicomponent cathode materials for sodium ion batteries by exploring three-dimensional compositional heterogeneities

Affordable sodium ion batteries hold great promise for revolutionizing stationary energy storage technologies. Sodium layered cathode materials are usually multicomponent transition metal (TM) oxides and each TM plays a unique role in the operating cathode chemistry, e.g., redox activity, structural stabilization. Engineering the three-dimensional (3D) distribution of TM cations in individual cathode particles can take advantage of a depth-dependent charging mechanism and enable a path towards tuning local TM–O chemical environments and building resilience against cathode–electrolyte interfacial reactions that are responsible for capacity fading, voltage decay and safety hazards. In this study, we create 3D compositional heterogeneity in a ternary and biphasic (O3–P3) sodium layered cathode material (Na 0.9 Cu 0.2 Fe 0.28 Mn 0.52 O 2 ). The cells containing this material deliver stable voltage profiles, and discharge capacities of 125 mA h g –1 at C/10 with almost no capacity fading after 100 cycles and 75 mA h g –1 at 1C with negligible capacity fading after 200 cycles. The direct performance comparison shows that this material outperforms other materials with similar global compositions but different mesoscale chemical distributions. Synchrotron X-ray spectroscopy/imaging and density functional theory studies reveal depth-dependent chemical environments due to changes to factors such as charge compensation and strength of orbital hybridization. Finally, 3D spectroscopic tomography illuminates the path towards optimizing multicomponent sodium layered cathode materials, to prevent the migration of TMs upon prolonged cycling. Furthermore, the study reports an inaugural effort of multifaceted and counterintuitive investigation of sodium layered cathode materials and strongly implies that there is plenty of room at the bottom by tuning nano/meso scale chemical distributions for stable cathode chemistry.

25 ENERGY STORAGE↗
DOE OSTI2018

A new elliptical-beam method based on time-domain thermoreflectance (TDTR) to measure the in-plane anisotropic thermal conductivity and its comparison with the beam-offset method

Materials lacking in-plane symmetry are ubiquitous in a wide range of applications such as electronics, thermoelectrics, and high-temperature superconductors, in all of which the thermal properties of the materials play a critical part. Yet, very few experimental techniques can be used to measure in-plane anisotropic thermal conductivity. A beam-offset method based on time-domain thermoreflectance (TDTR) was previously proposed to measure in-plane anisotropic thermal conductivity. However, a detailed analysis of the beam-offset method is still lacking. Our analysis shows that uncertainties can be large if the laser spot size or the modulation frequency is not properly chosen. In this report we propose an differing approach based on TDTR to measure in-plane anisotropic thermal conductivity using a highly elliptical pump (heating) beam. The highly elliptical pump beam induces a quasi-one-dimensional temperature profile on the sample surface that has a fast decay along the short axis of the pump beam. The detected TDTR signal is exclusively sensitive to the in-plane thermal conductivity along the short axis of the elliptical beam. By conducting TDTR measurements as a function of delay time with the rotation of the elliptical pump beam to different orientations, the in-plane thermal conductivity tensor of the sample can be determined. In this work, we first conduct detailed signal sensitivity analyses for both techniques and provide guidelines in determining the optimal experimental conditions. We then compare the two techniques under their optimal experimental conditions by measuring the in-plane thermal conductivity tensor of a ZnO [11-20] sample. The accuracy and limitations of both methods are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Confinement in Wendelstein 7-X Limiter Plasmas

Observations on confinement in the first experimental campaign on the optimized Stellarator Wendelstein 7-X are summarized. In this phase W7-X was equipped with five inboard limiters only and thus the discharge length restricted to avoid local overheating. Stationary plasmas are limited to low densities <2–3 centerdot 10 19 m -3 . With the available 4.3 MW ECR Heating core T e ~ 8 keV, T i ~ 1–2 keV are achieved routinely resulting in energy confinement time τ E between 80 ms to 150 ms. For these conditions the plasmas show characteristics of core electron root confinement with peaked T e -profiles and positive E r up to about half of the minor radius. Lastly, profiles and plasma currents respond to on- and off-axis heating and co- and counter ECCD respectively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncer- tainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2026

Sapphire Substrate Trenching to Advance Superconducting High-Coherence Quantum Devices

Achieving longer coherence times in superconducting qubits is essential for advancing quantum information processing and enabling scalable quantum computing. This work presents an innovative fabrication strategy focused on sapphire trenching of the substrate of superconducting high-coherence quantum devices, developed by the SQMS Nanofabrication Taskforce in collaboration with the materials characterization team. In this talk, we present a method to efficiently and consistently trench into the sapphire substrate, without compromising the surface roughness or profile of the etched sapphire. In the literature, trenching in the substrate has been shown to decrease losses, unwanted coupling and thermal stress. Sapphire’s strong covalent bonds make it harder to etch compared to silicon, yet it is more favorable for high-coherence quantum devices due to its lower dielectric losses. This innovative technique opens new possibilities for superconducting qubit fabrication: we fabricated high coherence qubit chips on sapphire substrates with trenching, to demonstrate that it will help pushing towards higher coherence times. By integrating this work with ongoing junction process optimization, design innovation, materials characterization and exploration, we outline a clear pathway toward transmon coherence times reaching millisecond scales and beyond.

Garattoni, S. [Fermilab]↗
DOE OSTI2026

Sapphire Substrate Trenching to Advance Superconducting High-Coherence Quantum Devices

Achieving longer coherence times in superconducting qubits is essential for advancing quantum information processing and enabling scalable quantum computing. This work presents an innovative fabrication strategy focused on sapphire trenching of the substrate of superconducting high-coherence quantum devices, developed by the SQMS Nanofabrication Taskforce in collaboration with the materials characterization team. In this talk, we present a method to efficiently and consistently trench into the sapphire substrate, without compromising the surface roughness or profile of the etched sapphire. In the literature, trenching in the substrate has been shown to decrease losses, unwanted coupling and thermal stress. Sapphire’s strong covalent bonds make it harder to etch compared to silicon, yet it is more favorable for high-coherence quantum devices due to its lower dielectric losses. This innovative technique opens new possibilities for superconducting qubit fabrication: we fabricated high coherence qubit chips on sapphire substrates with trenching, to demonstrate that it will help pushing towards higher coherence times. By integrating this work with ongoing junction process optimization, design innovation, materials characterization and exploration, we outline a clear pathway toward transmon coherence times reaching millisecond scales and beyond.

Garattoni, S. [Fermilab]↗
DOE OSTI2021

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

The study presented here focuses on performance characteristics and trade-offs associated with running machine-learning tasks in multi-GPU environments on both on-site cloud computing resources and commercial cloud services (Azure). Specifically, this study examines these tradeoffs by examining the performance of training and fine-tuning of transformer-based deep-learning (DL) networks on clinical notes and data, a task of critical importance in the medical domain. To this end, we perform DL-related experiments on the widely deployed NVIDIA V100 GPUs and on the newer A100 GPUs connected via NVLink or PCIe. This study analyzes the execution time of major operations to train DL models and investigate popular options to optimize each of them. We examine and present the findings on the impacts that various operations (e.g. data loading into GPUs, training, fine-tuning), optimizations, and system configurations (single vs. multi-GPU, NVLink vs. PCIe) have on the overall training performance.

Begoli, Edmon↗
DOE OSTI2020

Integrating Electric Vehicle Charging Infrastructure into Commercial Buildings and Mixed-Use Communities: Design, Modeling, and Control Optimization Opportunities: Preprint

This paper discusses modeling and field studies of controlled EV charging that have been performed with the goal of minimizing requirements for infrastructure upgrades, minimizing building peak demand charges, and maximizing the use of on-site generation. We present a large-scale workplace charging pilot of a demand-controlled scheduled EV charging system with over 250 active daily commuters, successfully demonstrating management of aggregate charging power to avoid new infrastructure investments, mitigate peak demand charges, and provide cost-effective workplace charging to users. In addition to understanding opportunities for demand management, integrating these controllable loads into the energy modeling process for new buildings will also be necessary. This paper then presents an example energy modeling process that evaluates the potential effects of EV charging on building load profiles and infrastructure requirements for a mixed-use community. Finally, we discuss an illustration of how EV charging can be controlled to be synergistic with other building loads and distributed generation.

buildings↗
DOE OSTI2019

On the memory attribution problem: A solution and case study using MPI

As parallel applications running on large–scale computing systems become increasingly memory constrained, the ability to attribute memory usage to the various components of the application is becoming increasingly important. We present the design and implementation of memnesia, a novel memory usage profiler for parallel and distributed message–passing applications. Our approach captures both application– and message–passing library–specific memory usage statistics from unmodified binaries dynamically linked to a message–passing communication library. Using microbenchmarks and proxy applications, we evaluated our profiler across three Message Passing Interface (MPI) implementations and two hardware platforms. Furthermore, the results show that our approach and the corresponding implementation can accurately quantify memory resource usage as a function of time, scale, communication workload, and software or hardware system architecture, clearly distinguishing between application and MPI library memory usage at a per–process level. With this new capability, we show that job size, communication workload, and hardware/software architecture influence peak runtime memory usage. In practice, this tool provides a potentially valuable source of information for application developers seeking to measure and optimize memory usage.

97 MATHEMATICS AND COMPUTING↗