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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamics Informed Optimization for Resilient Energy Systems

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the Western System Coordinating Council (WSCC) 9-bus test system using synthetic multi-device outage scenarios. Towards integrating our modeling framework with real threats and more realistic power systems, we explore applying hybrid dynamics to power systems. Our work is applied to basic RL circuits with the ultimate goal of using the methodology to model protective tripping schemes in the grid. Finally, we survey mitigation techniques for HEMP threats and describe a GIS application developed to create threat scenarios in a grid with geographic detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A mechanistic model for creep and thermal aging in Alloy 709

This report describes a physics-based model for creep and thermal aging in Alloy 709. Alloy 709 is an advanced austenitic alloy, targeted for use in future Sodium Fast Reactors (SFRs) and other advanced reactors. The material has superior high temperature properties compared to currently qualified 316 and 304 stainless steels. However, the available creep and thermal aging test database for Alloy 709 is significantly more limited compared to the historical materials. The physics-based model developed here is one way to accelerate the qualification of the material by providing more accurate long-term predictions for creep properties and thermal aging, compared to current empirical time-extrapolate techniques. The crystal plasticity finite element model is used to predict the deformation and failure of alloy 709. The same setup for the CPFE model is used in both the baseline model calibration process and the simulation campaigns for parameter inference. Specific constitutive choices are made for Alloy 709 to capture the primary deformation mechanisms. The dislocation creep formulation developed by Hu and Cocks is extended to account for coupled precipitation formation and the grain boundary cavitation model developed by Sham, Needleman, et al. is used to model grain boundary cavitation-induced failure. A novel update algorithm is proposed to render the semi-discrete constitutive update for the Sham-Needleman model unconditionally stable. A progressive calibration approach is adopted based on the observations that several types of material responses can be effectively decoupled. A surrogate model is trained based on full-fledged CPFE simulations to accelerate the forward model evaluations, and stochastic variational inference (SVI) is used to calibrate the unknown microstructural model parameters. The calibrated mechanistic model is used to predict the long-term creep life of Alloy 709, and the predictions are compared against classical empirical approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sierra/SolidMechanics 5.16 Capabilities in Development Manual

This user’s guide documents capabilities in Sierra/SolidMechanics which remain “in-development” and thus are not tested and hardened to the standards of capabilities listed in Sierra/SM 5.16 User’s Guide. Capabilities documented herein are available in Sierra/SM for experimental use only until their official release. These capabilities include, but are not limited to, novel discretization approaches such as the conforming reproducing kernel (CRK) method, numerical fracture and failure modeling aids such as the extended finite element method (XFEM) and J-integral, explicit time step control techniques, dynamic mesh rebalancing, as well as a variety of new material models and finite element formulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Clinical effects of 3D printing-assisted posterolateral incision in the treatment of ankle fractures involving the posterior malleolus

Objective To explore the clinical outcomes of a 3D printing-assisted posterolateral approach for the treatment of ankle fractures involving the posterior malleolus. Methods A total of 51 patients with ankle fractures involving the posterior malleolus admitted to our hospital from January 2018 to December 2019 were selected. The patients were divided into 3D printing group (28 cases) and control group (23 cases). 3D printing was performed for ankle fractures, followed by printing of a solid model and simulation of the operation on the 3D model. The operation was then performed according to the preoperative plan, including open reduction and internal fixation via the posterolateral approach with the patient in the prone position. Routine x-ray and CT examinations of the ankle joint were performed, and ankle function was evaluated using the American Foot and Ankle Surgery Association (AOFAS) ankle-hindfoot score. Results All patients underwent x-ray and CT examinations. All fractures healed clinically, without loss of reduction or failure of internal fixation. Good clinical effects were achieved in both groups of patients. The operation time, intraoperative blood loss and intraoperative fluoroscopy frequency in the 3D printing group were significantly less than those in the control group ( p < 0.05). There was no significant difference between the two groups in the anatomical reduction rate of fractures or the incidence of surgical complications ( p > 0.05). Conclusion The 3D printing-assisted posterolateral approach is effective in the treatment of ankle fractures involving the posterior malleolus. The approach can be well planned before the operation, is simple to perform, yields good fracture reduction and fixation, and has good prospects for clinical application.

Zheng, Hongming↗
DOE OSTI2022

Temperature Dependence of Structural Relaxation in Glass-Forming Liquids and Polymers

Understanding the microscopic mechanism of the transition of glass remains one of the most challenging topics in Condensed Matter Physics. What controls the sharp slowing down of molecular motion upon approaching the glass transition temperature T g , whether there is an underlying thermodynamic transition at some finite temperature below T g , what the role of cooperativity and heterogeneity are, and many other questions continue to be topics of active discussions. This review focuses on the mechanisms that control the steepness of the temperature dependence of structural relaxation (fragility) in glass-forming liquids. We present a brief overview of the basic theoretical models and their experimental tests, analyzing their predictions for fragility and emphasizing the successes and failures of the models. Special attention is focused on the connection of fast dynamics on picosecond time scales to the behavior of structural relaxation on much longer time scales. A separate section discusses the specific case of polymeric glass-forming liquids, which usually have extremely high fragility. We emphasize the apparent difference between the glass transitions in polymers and small molecules. We also discuss the possible role of quantum effects in the glass transition of light molecules and highlight the recent discovery of the unusually low fragility of water. At the end, we formulate the major challenges and questions remaining in this field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Mitigating commutation failures in HVDC systems with SFCL deployment

Commutation failures represent a prevalent issue encountered in line-commutated-converter high voltage direct current (LCC-HVDC) systems. As the widespread deployment of HVDC systems continues, the risk associated with commutation failures increases, posing a growing threat to power grids due to their potential to trigger severe consequences, including cascading failures and widespread blackouts. This research paper aims to address the significant issue of commutation failure within direct current (DC) systems through advocating for the use of resistive-type Superconducting Fault Current Limiters (R-SFCLs). To substantiate the efficacy of this proposed strategy, an array of simulations are executed using the PSCAD/EMTDC software. This comprehensive study investigates the performance characteristics of R-SFCLs configured with varying resistance values, scrutinizing their response under diverse fault resistance scenarios and distinct fault initiation times within the LCC-HVDC system. The outcomes of these simulations are that SFCLs confer significant advantages for mitigating commutation failures, surpassing traditional mitigation methods in terms of effectiveness. Consequently, SFCLs emerge as an optimal solution to prevent commutation failures in the HVDC systems.

Commutation failure↗
DOE OSTI2026

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
DOE OSTI2020

3D Coded SUMMA: Communication-Efficient and Robust Parallel Matrix Multiplication

In this paper, we propose a novel fault-tolerant parallel matrix multiplication algorithm called 3D Coded SUMMA that achieves higher failure-tolerance than replication-based schemes for the same amount of redundancy. This work bridges the gap between recent developments in coded computing and fault-tolerance in high-performance computing (HPC). The core idea of coded computing is the same as algorithm-based fault-tolerance (ABFT), which is weaving redundancy in the computation using error-correcting codes. In particular, we show that MatDot codes, an innovative code construction for parallel matrix multiplications, can be integrated into three-dimensional SUMMA (Scalable Universal Matrix Multiplication Algorithm [30]) in a communication-avoiding manner. To tolerate any two node failures, the proposed 3D Coded SUMMA requires ~50% less redundancy than replication, while the overhead in execution time is only about 5–10%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dispersion curve regression – assisted wideband local wavenumber analysis for characterizing three-dimensional (3D) profile of hidden corrosion damage

Corrosion as common damage in civil, petrochemical, nuclear, and aerospace structures affects the integrity and safety of the structures and may lead to catastrophic failures. This paper presents dispersion curve regression-assisted local wavenumber analysis method, which can analyze the time–space wavefield containing wideband information of wave-damage interaction and further extract the structural information carried by such wavefield for characterizing hidden corrosion damage in an isotropic plate. To acquire the time–space wavefield, a noncontact scanning laser Doppler vibrometer is used. In our analysis method, the acquired time–space wavefield is firstly processed to generate a local wavenumber function. The derived wavenumber function is further analyzed with a dispersion curve regression step, which searches in a set of theoretical frequency-wavenumber dispersion curves for different plate thicknesses and identifies the optimal plate thickness whose theoretical curve best matches the frequency-wavenumber relation contained in the local wavenumber function. By this means, a 3D profile including both in plane and thickness dimensions of the structure can be constructed for corrosion visualization and quantification. The experimental study demonstrates that our method can quantify the profile of hidden uniform corrosion in metal plates in terms of its in-plane shape and size as well as its out-of-plane depth in the subwavelength scale. Moreover, compared to previous Lamb wave-based corrosion inspection methods, our technique allows for noncontact 3D characterization of hidden corrosion from a far distance to the structure. Finally, we believe this work will inspire new 3D damage quantification methods that are based on wavefield analysis as well as enable potential applications for the quantification of hidden corrosion in civil, petrochemical, nuclear, and aerospace structures.

42 ENGINEERING↗
DOE OSTI2021

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction

Progress in numerical weather and climate prediction accuracy greatly depends on the growth of the available computing power. As the number of cores in top computing facilities pushes into the millions, increased average frequency of hardware and software failures forces users to review their algorithms and systems in order to protect simulations from breakdown. This report surveys hardware, application-level and algorithm-level resilience approaches of particular relevance to time-critical numerical weather and climate prediction systems. A selection of applicable existing strategies is analysed, featuring interpolation-restart and compressed checkpointing for the numerical schemes, in-memory checkpointing, user-level failure mitigation and backup-based methods for the systems. Numerical examples showcase the performance of the techniques in addressing faults, with particular emphasis on iterative solvers for linear systems, a staple of atmospheric fluid flow solvers. The potential impact of these strategies is discussed in relation to current development of numerical weather prediction algorithms and systems towards the exascale. Trade-offs between performance, efficiency and effectiveness of resiliency strategies are analysed and some recommendations outlined for future developments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Use of Machine Learning for Signature Development in a Multi-Sensor Environment for Safeguard Applications of Solvent Extraction Processes

Idaho National Laboratory is constructing the Special Nuclear Material test bed (Beartooth) for research and development pertaining to nuclear fuel processing operations using centrifugal contactors. Beartooth will enable give researchers the opportunity to study the dissolution, separation, and conversion of special nuclear materials (e.g., plutonium, enriched uranium, and thorium). As a lead-in to Beartooth, this project constructed a test bed to study the process and equipment behavior with real time series data collection using a variety of non-traditional sensors, in order to identify process failures and label them as either accidental or purposeful, thus enhancing nuclear nonproliferation stewardship. The measurement sources in this test bed include vibration, acoustic, current, flow, colorimetric, and thermal data. These measurements vary in terms of magnitude, frequency, and location. This information will be combined and used within data-driven machine-learning methods to detect operation condition changes that are either intentional (i.e., changes in operating set points) or malicious (i.e., flow diversion) in nature. This presentation covers the data processing and signature development activities necessary for utilizing this heterogeneous dataset to classify process anomalies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Direct observation of strain-enhanced hydrogen segregation and failure at high-angle grain boundaries in nickel

Understanding the mechanisms underlying hydrogen embrittlement remains difficult, even in single-element metals. Both microstructure and stress state influence hydrogen distribution in metals and alloys, which impacts deformation and failure. Here, in this work, we use in-situ Kelvin probe force microscopy (KPFM) to monitor the hydrogen distribution in pure nickel over time at 1.1 % and 3.5 % strain. The sample strained to 3.5 % results in preferential hydrogen segregation to high-angle grain boundaries whereas the sample strained to 1.1 % does not exhibit preferential hydrogen segregation. Optical digital image correlation (DIC) shows that hydrogen charging results in both localized and reduced strains during tensile testing of a notched sample. Later stages of deformation and failure (e.g. microcracking) are studied by using in-situ transmission X-ray microscopy (TXM). TXM reveals nanoscale structural changes to a propagating crack in a hydrogen environment. Localized void growth and secondary cracking occur at grain boundaries near the primary crack front. Correlative electron backscattering diffraction (EBSD) is used to relate the cracking at grain boundaries to the hydrogen segregation observed in KPFM. These findings are unified in a proposed hydrogen embrittlement mechanism that describes the interaction of hydrogen with grain boundaries, and the role of grain boundaries in hydrogen embrittlement.

Grain boundary fracture↗
DOE OSTI2022

Development and performance of INCONEL® alloy 740H® seam-welded piping

INCONEL® alloy 740H® is an age-hardenable nickel-based alloy approved for pressure vessels and piping within ASME Section I, VIII, and B31.1. Currently, the code applies a weld strength reduction factor (WSRF) of 0.7 to the allowable stresses for longitudinal seam welds in the time dependent creep regime. In this work, a full-scale seam weld was successfully produced using typical industrial practices. The component was solution heat-treated and aged after fabrication to improve the performance of the weldment. Tensile, bend, impact, and low-cycle fatigue tests showed the component met all the specification requirements and elevated temperature properties were within base metal expectations with failures predominately in the weld metal. Long-term creep tests, including large samples more representative of the entire weldment, were fabricated and tested to times in excess of 10,000 h at multiple temperatures. Analysis of the creep data supports a WSRF of 0.9 for the solution annealed + aged weldments in contrast to the WSRF of 0.7 currently applied to welded + aged weldments. Metallurgical analysis shows that the solution annealing causes recrystallization of the weld metal and reduces the chemical compositional and microstructural gradients in the weldments resulting in acceptable short-term performance. In long-term creep, evidence for coarsened zones in the weldments due to discontinuous coarsening reactions were identified as the mechanism leading to accelerated creep damage formation in the weld metal and sample failure.

14 SOLAR ENERGY↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗
DOE OSTI2021

Preventing Failures By Dataset Shift Detection in Safety-Critical Graph Applications

Dataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Amyloidogenesis: What Do We Know So Far?

The study of protein aggregation, and amyloidosis in particular, has gained considerable interest in recent times. Several neurodegenerative diseases, such as Alzheimer’s (AD) and Parkinson’s (PD) show a characteristic buildup of proteinaceous aggregates in several organs, especially the brain. Despite the enormous upsurge in research articles in this arena, it would not be incorrect to say that we still lack a crystal-clear idea surrounding these notorious aggregates. In this review, we attempt to present a holistic picture on protein aggregation and amyloids in particular. Using a chronological order of discoveries, we present the case of amyloids right from the onset of their discovery, various biophysical techniques, including analysis of the structure, the mechanisms and kinetics of the formation of amyloids. We have discussed important questions on whether aggregation and amyloidosis are restricted to a subset of specific proteins or more broadly influenced by the biophysiochemical and cellular environment. The therapeutic strategies and the significant failure rate of drugs in clinical trials pertaining to these neurodegenerative diseases have been also discussed at length. At a time when the COVID-19 pandemic has hit the globe hard, the review also discusses the plausibility of the far-reaching consequences posed by the virus, such as triggering early onset of amyloidosis. Finally, the application(s) of amyloids as useful biomaterials has also been discussed briefly in this review.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling starch dynamics from seasonal variations of photosynthesis, growth and respiration

Abstract Nonstructural carbohydrates (NSCs) buffer differences in plant carbon supply (photosynthesis) and demand (respiration, growth, etc.), but the regulation of their dynamics remains unresolved. Seasonal variations in NSCs are well-documented, but differences in the time-average, amplitude, phase and other characteristics across ecosystems and functional types lack explanation; furthermore, observed dynamics do not always match expectations. The failure to match observed and expected dynamics has stimulated debate on whether carbon supply or demand drives NSC dynamics. To gain insight into how carbon supply and demand drive seasonal NSC dynamics, we derive a simple model of NSC dynamics based on carbon mass balance and linearizing the NSC demand to determine how supply-driven and demand-driven seasonal NSC dynamics differ. We find that supply-driven and demand-driven dynamics yield distinct timings of seasonal extrema, and supply overrides demand when carbon supply is low in winter (e.g., at high latitudes). Our results also suggest that NSC dynamics often lag changes carbon mass balance. We also predict differences in NSC dynamics across mass, suggesting that saplings are more dynamic and respond more quickly to the environment than mature trees. Our findings suggest that substrate-dependent regulation with environmental variation is sufficient to generate complex NSC dynamics.

Forestry↗
DOE OSTI2024

Cy-Phy ADS: Cyber Physical Anomaly Detection Framework for EV Charging Systems

Today’s large-scale Electric Vehicle (EV) infrastructures are heavily dependent on information communication technologies to maintain their operation and to support communication within sub-system components as well as the outside world. These technologies are vulnerable to various cyber and physical threats. Timely identification and mitigation of these threats are critical for improving human safety, avoiding economic losses, and preventing catastrophic system failures. By addressing this, our work presents a ResNet Autoencoder (AE) based Cyber-Physical Anomaly Detection System (Cy-Phy ADS) for detecting anomalies in EV Controller Area Network (CAN) protocol communication. It consists of four main components: Cyber-Physical Feature Extractor, ResNet AE-based Anomaly Detection Framework, Cyber-Physical Health Metric (CPHM), and Visualization Dashboard. The presented framework was trained and tested using CAN data collected from the EV charging system testbed at the Idaho National Laboratory. The presented Cy-Phy ADS compared against six widely used unsupervised anomaly detection algorithms: One Class Support Vector Machine (OCSVM), Variational Autoencoder (VAE), LSTM Autoencoder (LSTM AE), Isolation Forest (IForest), Principle Component Analysis (PCA) and Local Outlier Factor (LOF). Here the presented approach showed the highest accuracy among the compared methods. Further, the proposed approach showed comparable performance in terms of precision, F1, and False positive rate. It also showed the lowest training and inference time compared to the neural network-based baseline algorithms compared against with. Additionally, the Cy-Phy ADS has advantages such as unsupervised training, the ability to provide a holistic metric for system health characterization, and non-linear feature extraction.

99 GENERAL AND MISCELLANEOUS↗