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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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Conference paper titled, Comparing microclimate weather conditions from the weather research and forecasting (WRF) model with typical meteorological year (TMY) data for building energy simulations accepted for Building Simulation 2025 Conference in Brisbane, Australia in Aug 2025.
We calculate the seasonal changes that are largely associated with the half-yearly wave, autocorrelation functions, and the mean planetary waves in the monthly mean sea level pressure from two data sources. One covers the period from 1951 to 1958 (from the South African Weather Bureau) and the other the period from 1972 to 1980 (from the Australian Bureau of Meteorology). Thirty years of data from stations over the southern hemisphere are used to assess the reliability of the differences between the two periods that the grid-point data show. These differences are especially large over the Atlantic Ocean and the Pacific Ocean. The station data confirm the changes between the two periods and thus the observed differences in the mean waves, which are especially large for wave number 3.
In response to concerns about risks from lead-free induced faults to high reliability products, NASA has initiated a multi-year project to provide manufacturers and users with data to clarify the risks of lead-free materials in their products. The project will also be of interest to component manufacturers supplying to high reliability markets. The project was launched in November 2006. The primary technical objective of the project is to undertake comprehensive testing to generate information on failure modes/criteria to better understand the reliability of: (1) Packages (e.g., Thin Small Outline Package [TSOP], Ball Grid Array [BGA], Plastic Dual In-line Package [PDIP]) assembled and reworked with solder interconnects consisting of lead-free alloys (2) Packages (e.g., TSOP, BGA, PDIP) assembled and reworked with solder interconnects consisting of mixed alloys, lead component finish/lead-free solder and lead-free component finish/SnPb solder
The primary technical objective of this project is to undertake comprehensive testing to generate information on failure modes/criteria to better understand the reliability of: (1) Packages (e.g., Thin Small Outline Package [TSOP], Ball Grid Array [BGA], Plastic Dual In-line Package [PDIP]) assembled and reworked with lead-free alloys, (2) Packages (e.g., TSOP, BGA, PDIP) assembled and reworked with mixed (lead/lead-free) alloys.
In this paper we discuss our experiences with Navier-Stokes (NS) codes using central differencing (CD) and scalar artificial dissipation (SAD). The NS-CDSAD codes have been developed by several researchers. Our results confirm that for typical commercial transport wing and wing/body configurations flying at transonic conditions with all turbulent boundary layers, NS-CDSAD codes, when used with the Johnson-King turbulence model, are capable of computing pressure distributions in excellent agreement with experimental data. However, results are not as good when laminar boundary layers are present. Exhaustive 2-D grid refinement studies supported by detailed analysis suggest that the numerical errors associated with SAD severely contaminate the solution in the laminar portion of the boundary layer. It is left as a challenge to the CFD community to find and fix the problems with Navier-Stokes codes and to produce a NS code which converges reliably and properly captures the laminar portion of the boundary layer on a reasonable grid.
Type-5 wind turbines are unique in their use of a permanent magnet synchronous generator, as well as their use of a hydraulic torque converter. This architecture presents an opportunity to provide steady and grid-ready energy without the need for a power converter. With infrastructure continuity and reliability being an important topic amongst renewable energies, researchers have been prompted to further investigate the benefits of type-5 turbines’ unique electromechanical configuration on stable electricity generation. Researchers involved in the WindSG project, SG standing for synchronous generator, are aiming to model a type-5 turbine using Real Time Digital Simulation (RTDS) to evaluate its efficacy in the grid. RSCAD, the software run on the RTDS, comes pre-loaded with electrical and electromechanical components to help simulate electrical generation and grid conditions. However, within this repertoire there is a lack of a component to represent a gearbox with high-fidelity. Within RSCAD’s case studies, the gearbox is often represented simply by a gear ratio value. This presented the task of developing a high-fidelity gearbox model in RSCAD for use in the larger RTDS type-5 wind turbine model. This poster describes a method of developing a lumped parameter mathematical model to represent a planetary-parallel-parallel gearbox in RSCAD for use in RTDS.
Type-5 wind turbines are unique in their use of a permanent magnet synchronous generator, as well as their use of a hydraulic torque converter. This architecture presents an opportunity to provide steady and grid-ready energy without the need for a power converter. With infrastructure continuity and reliability being an important topic amongst renewable energies, researchers have been prompted to further investigate the benefits of type-5 turbines’ unique electromechanical configuration on stable electricity generation. Researchers involved in the WindSG project, SG standing for synchronous generator, are aiming to model a type-5 turbine using Real Time Digital Simulation (RTDS) to evaluate its efficacy in the grid. RSCAD, the software run on the RTDS, comes pre-loaded with electrical and electromechanical components to help simulate electrical generation and grid conditions. However, within this repertoire there is a lack of a component to represent a gearbox with high-fidelity. Within RSCAD’s case studies, the gearbox is often represented simply by a gear ratio value. This presented the task of developing a high-fidelity gearbox model in RSCAD for use in the larger RTDS type-5 wind turbine model. This presentation describes a method of developing a lumped parameter mathematical model to represent a planetary-parallel-parallel gearbox in RSCAD for use in RTDS.
The threat of geomagnetic disturbances (GMDs) to the reliable operation of the bulk energy system has spurred the development of effective strategies for mitigating their impacts. One such approach involves placing transformer neutral blocking devices, which interrupt the path of geomagnetically induced currents (GICs) to limit their impact. The high cost of these devices and the sparsity of transformers that experience high GICs during GMD events, however, calls for a sparse placement strategy that involves high computational cost. To address this challenge, we developed a physics-informed heterogeneous graph neural network (PIHGNN) for solving the graph-based dc-blocker placement problem. Our approach combines a heterogeneous graph neural network (HGNN) with a physics-informed neural network (PINN) to capture the diverse types of nodes and edges in ac/dc networks and incorporates the physical laws of the power grid. We train the PIHGNN model using a surrogate power flow model and validate it using case studies. Results demonstrate that PIHGNN can effectively and efficiently support the deployment of GIC dc-current blockers, ensuring the continued supply of electricity to meet societal demands. Furthermore, our approach has the potential to contribute to the development of more reliable and resilient power grids capable of withstanding the growing threat that GMDs pose.
he high penetration of inverter-based resources (IBRs) introduces new challenges to power systems due to the complex inverter control. However, IBRs can be configured to maximize their benefits to improve system resilience and reliability. This paper proposes a steady-state optimization model that aims to mitigate transmission congestion in a 100% grid- forming (GFM) IBR-based power system. This goal is achieved by determining the optimal droop settings for the GFM IBRs under different congestion conditions due to renewable energy and load variations. The numerical solution is rigorously verified by a high-fidelity model of the IEEE 39-bus test system with detailed GFM IBR control in the time-domain electromagnetic transient (EMT) simulation tool PSCAD. The numerical solution and simulation results show a significant congestion reduction while meeting all other operating requirements. It is also observed that the numerical solving time is substantially less compared to the EMT simulation time.
Plug-in electric vehicles (EVs) are reshaping the transportation energy landscape, providing a practical alternative to petroleum fuels for a growing number of applications. EV sales grew 55x in the past decade (2014-2024) and 6x since 2020, driven by technological progress enabled by policies to reduce transportation emissions as well as industrial plans motivated by strategic value of EVs for global competitiveness, jobs and geopolitics. In 2024, 22% of passenger cars sold globally were EVs and opportunities for EVs beyond on-road applications are growing, including solutions to electrify off-road vehicles, maritime and aviation. This Review updates and expands our 2020 assessment of the scientific literature and describes the current status and future projections of EV markets, charging infrastructures, vehicle-grid integration and supply chains in the USA. EV is the lowest-emission motorized on-road transportation option, with life-cycle emissions decreasing as electricity emissions continue to decrease. Charging infrastructure grew in line with EV adoption but providing ubiquitous reliable and convenient charging remains a challenge. EVs are reducing electricity costs in several US markets and coordinated EV charging can improve grid resilience and reduce electricity costs for all consumers. The current trajectory of technology improvement and industrial investments points to continued acceleration of EVs.
This paper provides the experimental test results of advanced CCGA packages tested in extreme temperature thermal environments. Standard optical inspection and x-ray non-destructive inspection tools were used to assess the reliability of high density CCGA packages for deep space extreme temperature missions. Ceramic column grid array (CCGA) packages have been increasing in use based on their advantages such as high interconnect density, very good thermal and electrical performances, compatibility with standard surface-mount packaging assembly processes, and so on. CCGA packages are used in space applications such as in logic and microprocessor functions, telecommunications, payload electronics, and flight avionics. As these packages tend to have less solder joint strain relief than leaded packages or more strain relief over lead-less chip carrier packages, the reliability of CCGA packages is very important for short-term and long-term deep space missions. We have employed high density CCGA 1152 and 1272 daisy chained electronic packages in this preliminary reliability study. Each package is divided into several daisy-chained sections. The physical dimensions of CCGA1152 package is 35 mm x 35 mm with a 34 x 34 array of columns with a 1 mm pitch. The dimension of the CCGA1272 package is 37.5 mm x 37.5 mm with a 36 x 36 array with a 1 mm pitch. The columns are made up of 80% Pb/20%Sn material. CCGA interconnect electronic package printed wiring polyimide boards have been assembled and inspected using non-destructive x-ray imaging techniques. The assembled CCGA boards were subjected to extreme temperature thermal atmospheric cycling to assess their reliability for future deep space missions. The resistance of daisy-chained interconnect sections were monitored continuously during thermal cycling. This paper provides the experimental test results of advanced CCGA packages tested in extreme temperature thermal environments. Standard optical inspection and x-ray non-destructive inspection tools were used to assess the reliability of high density CCGA packages for deep space extreme temperature missions. Keywords: Extreme temperatures, High density CCGA qualification, CCGA reliability, solder joint failures, optical inspection, and x-ray inspection.
High-resolution population modeling is important for supporting effective decision-making across diverse sectors. LandScan Mosaic generates population estimates at the level of individual buildings and aggregates them to 3 arc-second grids, and this approach performs well in regions where building footprint data are comprehensive and reliable. However, large portions of the globe still suffer from incomplete, sparse, or entirely missing building stock datasets, creating a structural limitation for strictly building-based population models. To address this research gap, this study proposes a computer vision-based framework that employs Google Earth Engine satellite embeddings and UNet, which allows us to directly impute grid-level population estimates in building-data-deficient areas. Applied to Taiwan as a case study, the framework achieved strong predictive performance with R$^{2}$ of 0.89, RMSE of 18.70, and MAE of 8.41, outperforming traditional machine learning approaches. Notably, the proposed framework effectively addressed building false-positive errors inherent in Global Human Settlement Layer (GHSL) data, correctly identifying uninhabited areas that were erroneously classified as populated. The framework also offers significant advantages for global population mapping, particularly in terms of scalability and temporal consistency, thereby extending the coverage and accuracy of high-resolution population products in data-scarce regions worldwide. Urban planners, decision makers, and related stakeholders can obtain granular population distributions to support more accurate and targeted infrastructure investment, service delivery, resource allocation, and risk assessment decisions.
Power electronics are increasingly being used to condition electricity for a wide array of applications, such as transportation (on land, air, and water), data centers, radio frequency, directed energy, wind, solar, and grid-tied applications. Here, to increase power density, performance, efficiency, and reliability-as well as to reduce cost-innovations and developments are needed in the multiphysics packaging of power electronics at a die, module, and converter level. This includes fundamental R&D related to emerging high-voltage, high-temperature, and high-switching-frequency power electronics, packaging materials, thermal materials and interfaces, fluid-based thermal management technologies, reliability, condition monitoring, and prognostics. Latest developments in this area are published as a Special Section on Multiphysics Aspects of Power Electronics Packaging. The first part was published in the May 2024 issue of the IEEE Transactions on Components, Packaging and Manufacturing Technology (Volume 14, Issue 5). The second part of that Special Section is being published in this issue. A brief summary of the papers included in the second part are given below.
This report provides an overview of real-time reliability study tools and their use by power system operators in the control room environment. After introducing some of the nuances of the control room environment and the differences in perspectives between power system engineers and operators, the roles and responsibilities of key entities involved in RTCA workflows are introduced. These are specifically the transmission system operator (TOP) and reliability coordinator (RC), which are required to run tools such as real-time contingency analysis (RTCA) as part of a real-time reliability assessment every 30 minutes, as dictated by a series of standards issued by the North American Electric Reliability Corporation (NERC). The process by which power systems operators operate the grid is discussed in terms of naturalistic decision making (NDM) and the recognition-primed decision-making (RPD) model. This cognitive model describe how experts working in high-risk, high-stress environments make safety-critical decisions under uncertainty and time pressure. For power system operators, the mental simulations involved in the traditional RPD model are supplemented by physics-based simulations using numerical tools, such as RTCA, to improve situational awareness and effectiveness of control actions. Next, a generic workflow is introduced to describe operator decision making for running RTCA tools and responding to system violations on a pre-contingent basis. The types of analysis performed and control actions chosen by power system operators are described in detail. The overall high-level workflow is then expanded in subsequent sections, with special attention given to high-voltage violations, low-voltage violations, and thermal overloads. Each type of violation is described in detail, with explanations of common causes, impacts on equipment and customers, and mitigation strategies. An additional workflow diagram is provided for each type of violation.
Reliable super-resolution methods are crucial for applications like remote sensing, grid resilience and disaster impact analysis, and standoff biometrics. These methods infuse additional high-frequency information into reconstructions, allowing for better contextualization and image intelligence. However, super-resolution models can also introduce hallucinations or other unseen vulnerabilities that could be exploited by an adversary. This is further compounded by the prominence of deep learning in these models, as models are often blindly applied on out-of-distribution images. In this work, we implement adversarial attacks in common open-source super-resolution models and examine their impact on reconstructions and downstream classification tasks. We find that an adversarially trained super-resolution model can produce high-quality reconstructions that degrade downstream classifications. Moreover, these attacks do not require access to low-resolution imagery or class labels at inference time. These results demonstrate the vulnerability of super-resolution methods to malicious actors and motivates the development of a detector for super-resolution adversarial attacks. Further exploration of adversarial attacks in this domain is required to ensure trustworthiness and robustness of super-resolution models for national security applications.
Artificial intelligence (AI) training data centers with periodic load profiles can induce sustained grid oscillations across a wide frequency range, making accurate monitoring essential for reliable power system operation. This report evaluates the adequacy of existing measurement systems for monitoring such oscillations, focusing on phasor measurement units (PMUs) and point-on-wave (POW) measurement systems. The analysis shows that while PMUs are highly effective for monitoring low-frequency electromechanical oscillations, they have inherent limitations in accurately representing higher-frequency oscillations due to constraints imposed by reporting rates and the bandwidth of phasor estimation filters. Even when configured with higher reporting rates, the filtering inherent in the phasor estimation process can significantly attenuate oscillation magnitudes, potentially leading to underestimation of oscillatory behavior. This has important implications for compliance and performance monitoring of large loads. To address the limitations associated with PMU-based monitoring, the report examines the use of high-resolution POW measurements, which can capture oscillations across a broader frequency range. However, continuous POW monitoring introduces practical challenges related to large data volumes, communication bandwidth, and real-time data processing. For this reason, the report also discusses emerging approaches that use POW measurements as a complementary capability alongside PMUs to improve observability of oscillations from large data center loads.
Inspection results along with SEM and optical cross-sectional photos revealing damage and failure mechanisms will also be presented.
The test results for numerous chip scale package assembly performed under MicrotypeBGA Consortium led by the Jet Propulsion Laboratory have been published previously.