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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs

The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.

Cybersecurity↗
DOE OSTI2021

Tri-Level Scheduling Model Considering Residential Demand Flexibility of Aggregated HVACs and EVs Under Distribution LMP

Residential loads, especially heating, ventilation and air conditioners (HVACs) and electric vehicles (EVs), have great potentials to provide demand flexibility which is an attribute of grid-interactive efficient buildings (GEB). Under this new paradigm, first, EV and HVAC aggregator models are developed in this paper to represent the fleet of GEBs, in which the aggregated parameters are obtained based on a new approach of data generation and least squares parameter estimation (DG-LSPE), which can deal with heterogeneous HVACs. Then, a tri-level bidding and dispatching framework is established based on competitive distribution operation with distribution locational marginal price (DLMP). Furthermore, the first two levels form a bilevel model to optimize the aggregators’ payment and to represent the interdependency between load aggregators and the distribution system operator (DSO) using DLMP, and the third level is to dispatch the optimal load aggregation to all residents by the proposed priority list-based demand dispatching algorithm. Finally, case studies on a modified IEEE 33-Bus system illustrate three main technical reasons of payment reduction due to demand flexibility: load shift, DLMP step changes, and power losses. They can be used as general guidelines for better decision-making for future planning and operation of demand response programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Robust Decentralized Learning Using ADMM With Unreliable Agents

Many signal processing and machine learning problems can be formulated as consensus optimization problems which can be solved efficiently via a cooperative multi-agent system. However, the agents in the system can be unreliable due to a variety of reasons: noise, faults and attacks. Providing erroneous updates leads the optimization process in a wrong direction, and degrades the performance of distributed machine learning algorithms. This paper considers the problem of decentralized learning using ADMM in the presence of unreliable agents. First, we rigorously analyze the effect of erroneous updates (in ADMM learning iterations) on the convergence behavior of the multi-agent system. We show that the algorithm linearly converges to a neighborhood of the optimal solution under certain conditions and characterize the neighborhood size analytically. Next, we provide guidelines for network design to achieve a faster convergence to the neighborhood. Here, we also provide conditions on the erroneous updates for exact convergence to the optimal solution. Finally, to mitigate the influence of unreliable agents, we propose ROAD , a robust variant of ADMM, and show its resilience to unreliable agents with an exact convergence to the optimum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario

Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish common ground among collaborators. The use of provenance to communicate analytic sensemaking carries promise by describing the interactions and summarizing the steps taken to reach insights. Yet, no universal guidelines exist for communicating provenance in different settings. Our work here focuses on the presentation of provenance information and the resulting conclusions reached and strategies used by new analysts. In an open-ended, 30-minute, textual exploration scenario, we qualitatively compare how adding different types of provenance information (specifically data coverage and interaction history) affects analysts' confidence in conclusions developed, propensity to repeat work, filtering of data, identification of relevant information, and typical investigation strategies. We see that data coverage (i.e., what was interacted with) provides provenance information without limiting individual investigation freedom. On the other hand, while interaction history (i.e., when something was interacted with) does not significantly encourage more mimicry, it does take more time to comfortably understand, as represented by less confident conclusions and less relevant information-gathering behaviors. In conclusion, our results contribute empirical data towards understanding how provenance summarizations can influence analysis behaviors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Clarifying Terminology in Microbial Ecology: A Call for Precision in Scientific Communication

The rapid evolution of microbiology as a field of research has led to the introduction of new terminology and the adaptation of existing terms. However, inconsistencies in the use of these terms, including variations across different scientific disciplines, can lead to confusion and miscommunication within the scientific community. This article discusses the importance of precise terminology in microbiome research, highlighting examples where terms have been misused or redefined without clear justification. We also present a list of frequently used terms in microbial ecology along with their specific definitions. We argue that the misuse of terminology can hinder scientific progress by creating ambiguity and misunderstanding. To address this, we propose a set of guidelines for the consistent use of key terms and provide clear definitions for some of the most commonly misused or newly introduced terms in the field. The definitions provided herein will also function as a guide for young researchers new to the field of microbial ecology. Accurate and consistent use of terminology is crucial for effective communication and collaboration in microbiology research. By adhering to standardised definitions, researchers can ensure that their work is clearly communicated and contributes meaningfully to the progress of science.

definitions↗
DOE OSTI2022

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

Abstract Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Implementation of early psychosis services in Latin America: A scoping review

Abstract Aim The evidence of the effectiveness and cost‐effectiveness of early intervention for psychosis (EIP) services has motivated their implementation worldwide. However, complex interventions of such EIP services require local adaptations to successfully match population needs and cultural differences. Latin America is a heterogenous region where EIP services are progressively being adopted. Our aim is to map such initiatives in the region with a focus on implementation outcomes. Methods A scoping review following the Preferred Reporting Items for Systematic review and Meta‐Analysis extension for Scoping Reviews guidelines was conducted. International and regional databases were searched for publications describing EIP programmes in the region. Besides mapping the services, we described implementation outcomes based on the Standards for Reporting Implementation Studies Checklist. Results Ten articles describing seven EIP initiatives from the region were found. Four countries were represented: Argentina, Brazil, Chile and Mexico. The implementation outcomes reporting was heterogenous, although it was possible to ascertain EIP services are feasible and adequate for the region's context. Also, there is some evidence of effectiveness in terms of reducing hospitalizations and improving symptoms. Information about fidelity measures was scarce and there was no information about costs or cost‐effectiveness. Conclusions Only a small proportion of Latin American countries have adopted EIP services. Although these programmes seem to be feasible and effective, data on other implementation outcomes, such as fidelity, cultural appropriateness, cost‐effectiveness and affordability are not available. This might in part explain why this effective approach has not been yet scaled‐up at nationwide levels.

Aceituno, David↗
DOE OSTI2026

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

Ecosystem models are increasingly central to the decision-making for environmental policy, conservation planning, and climate-related investments. Yet, the growing reliance on Multi-Model Ensembles (MMEs) of ecosystem models by practitioners and policymakers, sometimes under tight timelines and imperfect information, has frequently outpaced the scientific rigor required to ensure ensemble reliability. Here, MMEs refer to approaches that combine targeted predictions from multiple models with the expectation of improving robustness and quantifying predictive uncertainty. Poorly designed MMEs may create a false sense of confidence and lead to suboptimal policy and market decisions. This perspective argues that robust decision-making-relevant MMEs must be grounded on two pillars: (1) rigorous Model Intercomparison Projects (MIPs), which identify inter-model agreement and disagreement, characterize model uncertainties, and evaluate robustness with observationally based benchmarks—MIPs' diagnostic evaluation is so critical that it must be needed to drive MME's decision in model selection and weighting, especially when only a limited number of models available; and (2) co-design by both stakeholders and scientists to ensure that scenarios, metrics and uncertainty requirements provide decision-relevant information. Building upon the past success and lessons from the existing MIPs-MMEs efforts (e.g., climate/Earth system/crop), we derived the theoretical basis for MMEs, addressed their specific challenges in ecosystem modeling, and highlighted proper consideration of model numbers and diversity, risk of model inter-dependence, effective calibration of model parameters, possible overdue of some ecosystem model development, critical roles of open benchmark data across a wide range of conditions, and suggested use of Artificial Intelligence to support MIPs-MMEs. We highlighted the under-recognized opportunity for MIPs and MMEs to drive scientific progress and innovation through identifying better performing models, systematic benchmarking, feedback loops, and targeted model improvement. By following actionable best practice guidelines, MMEs can evolve from ad hoc aggregation of models into a trusted backbone of environmental policy and decision-making.

ecosystem modeling↗
DOE OSTI2021

Processing and 3D printing of SiCN polymer-derived ceramics

Preceramic polymer resins are attractive for the 3D printing of net-shaped ceramic components. Recently various processes have been demonstrated for 3D printing of polymer-derived ceramics (PDCs). Ultimately in these processes, the process outcomes strongly depend on the process parameters. In particular, for PDCs the ceramic density, and ceramic yield are affected by the catalyst concentration and cross-linking duration. Here, we use thermal analysis and FTIR to quantify the interrelation of the process parameters on the process outcome for polysilazanes and demonstrate 3D printing of PDC components based on the best-identified process parameters. Furthermore, the results of this work can be used as guidelines for future additive manufacturing of PDCs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Indoor air quality in new and renovated low-income apartments with mechanical ventilation and natural gas cooking in California

This work presents pollutant concentrations and performance data for code-required mechanical ventilation equipment in 23 low-income apartments at 4 properties constructed or renovated 2013-2017. All apartments had natural gas cooking burners. Occupants pledged to not use windows for ventilation during the study but several did. Measured airflows of range hoods and bathroom exhaust fans were lower than product specifications. Only eight apartments operationally met all ventilation code requirements. Pollutants measured over one week in each apartment included time-resolved fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), formaldehyde and carbon dioxide (CO 2 ) and time-integrated formaldehyde, NO 2 and nitrogen oxides (NO X ). Compared to a recent study of California houses with code-compliant ventilation, apartments were smaller, had fewer occupants, higher densities, and higher mechanical ventilation rates. Mean PM 2.5 , formaldehyde, NO 2 , and CO 2 were 7.7 µg/m 3 , 14.1 ppb, 18.8 ppb, and 741 ppm in apartments; these are 4% lower, 25% lower, 165% higher, and 18% higher compared to houses with similar cooking frequency. Four apartments had weekly PM 2.5 above the California annual outdoor standard of 12 µg/m 3 and also discrete days above the World Health Organization 24-h guideline of 25 µg/m 3 . Two apartments had weekly NO 2 above the California annual outdoor standard of 30 ppb.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Coinfection of Influenza A and B and Human OC43 Coronavirus in Normal Human Bronchial Epithelial Cells

Influenza viruses and seasonal coronaviruses are pathogens transmitted via an airborne route that can cause respiratory diseases in humans that have similar symptoms such as fever, cough, and pneumonia. These two viruses can infect similar human tissues, such as the respiratory tract and nasal, bronchial, and alveolar epithelial cells. Influenza virus and seasonal coronavirus coinfections are poorly understood. Here, we coinfected normal human bronchial epithelial (NHBE) cells with influenza A/California/04/09 (IAV) or B/Victoria/504/2000 (IBV) strains and the seasonal human beta-coronavirus OC43 and evaluated viral replication capacities. We also examined changes in the expression of various cytokines/chemokines by qPCR and Luminex assay. We observed that the replication of IAV and IBV was not affected by coinfection with OC43. However, coinfection reduced OC43 titers (~3-fold) compared with infection with OC43 alone. Select cytokine/chemokine expression was increased in coinfected cells compared with all single infections with greater differences seen between coinfected cells and cells infected with OC43 alone compared with IAV- or IBV-infected cells. In addition, IL-8 and IL-1RA showed the highest expression among a panel of 22 cytokines by Luminex. As the rate of influenza and seasonal coronavirus coinfection continue to increase, our findings may help set guidelines for the treatments of the individuals coinfected with both viruses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The influence of the processing parameters on the reactive flash sintering of ZrO 2 -CeO 2

Reactive flash sintering (RFS) is a method that was recently developed to produce dense single-phase bulk ceramic parts through solid-state reactions in a single-step that only takes a few minutes. The influence of the RFS parameters on the phase purity of a simple mixed oxide, (Zr 0.8 ,Ce 0.2 )O 2 , was investigated. Parameters such as furnace temperature, furnace atmosphere, electric current density, and alternating current (AC) or direct current (DC) were examined. It was found that (Zr 0.8 ,Ce 0.2 )O 2 pellets with high densities, above 90% of its theoretical density, can be produced by RFS in a few minutes when RFS occurs under oxidizing atmospheres, AC fields with current densities of 100 mA·mm –2 , and at a furnace temperature of 1200°C. Reducing conditions such as Ar-H 2 atmosphere and DC fields, low furnace temperatures, and low current densities resulted in phase impurities and poor reactions between the ZrO 2 and the CeO 2 powders. These results show that RFS is a useful method to produce mixed oxides, but it is very sensitive to the processing parameters. This is the first time that the influence of most of the RFS processing parameters has been studied systematically. Thus, the present work aims to provide guidelines on selecting the right processing parameters when exploring RFS.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Genetic identification of 91 poplar cultivars based on SSR markers

Accurate genetic identification and relationship analysis of poplar cultivars is necessary to establish commercial poplar plantations and select suitable breeding strategies. In this study, 91 poplar cultivars belonging to four sections (Aigeiros, Tacamahaca, Populus and Turanga) and inter/intra-sectional hybrids were genotyped using 18 polymorphic simple sequence repeat (SSR) markers. In total, 222 alleles were amplified with an average of 12.3 alleles per marker. The mean polymorphic information content and power of discrimination were 0.706 and 0.813, respectively. Five SSR markers (ORPM_103, ORPM_247, GCPM_1048, GCPM_1255 and LG_X_19) constituted a core fingerprint and were sufficient to identify all the tested cultivars. With some notable exceptions, cultivars of the same species generally clustered together in cluster (UPGMA) and ordination (PCO) analyses. Flow cytometry indicated that 11 poplar cultivars were triploid. Among these, seven had three alleles at some loci, suggesting that SSR markers could indicate the ploidy level to some extent. This study provides useful genetic information for the identification and protection of poplar cultivars in China and offers a guideline for the selection of poplar crossing parents based on ploidy level and genetic relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

“Figure‐of‐Eight” Suture‐Button Technique for Fixation of Displaced Anterior Cruciate Ligament Avulsion Fracture

Objective To assess the clinical results of the “figure‐of‐eight” suture‐button technique in the arthroscopic treatment of anterior cruciate ligament (ACL) tibial avulsion fractures. Methods This was a retrospective study reviewing data from September 2013 to June 2019. A total of 27 patients (13 males and 14 females) who underwent arthroscopic “figure‐of‐eight” suture‐button fixation for displaced ACL avulsion fractures were analyzed. The mean age of the patients in the sample was 15.8 years (10–29 years), with a mean follow‐up of 24 months (6–48 months). According to Meyers–McKeever classification, 11 patients were classified as type III and 16 as type IV. All patients were evaluated following the guidelines of the radiological union, the Lysholm knee scoring scale, and the International Knee Documentation Committee (IKDC). Results Fractures were united within 3 months after surgery in all 27 cases. During the last follow‐up, all the anterior drawer and Lachman tests were negative, except in 1 patient whose anterior drawer test was 1° positive. The range of motion was improved from 72.22° ± 27.92° before surgery to 137.78° ± 7.38° at the last follow‐up ( P < 0.05); the Lysholm score was improved from 45.81 ± 10.94 before surgery to 93.04 ± 5.66 at the last follow‐up ( P < 0.05); and the IKDC score was increased from 43.89 ± 11.16 before surgery to 90.26 ± 5.86 at the last follow‐up ( P < 0.05). In 1 patient, an inflammatory reaction was observed at the medial incision of the tibial tubercle; the symptoms disappeared with administration of antibiotics for 1 week. All patients returned to their preinjury physical activities at the last follow‐up. Conclusion The “figure‐of‐eight” suture‐button technique achieves a satisfactory clinical outcome and provides an effective method for the treatment of displaced ACL avulsion fractures.

Kuang, Shi‐da↗
DOE OSTI2025

Review of High‐Speed Digital Image Correlation: Advancements and Good Practices

This paper reviews the current state of the art in high‐speed (HS) and ultrahigh‐speed (UHS) digital image correlation (DIC) techniques, emphasizing their critical role in experimental research across various scientific domains. HS and UHS DIC have evolved significantly, driven by advancements in camera systems, image processing algorithms and experimental methodologies. These developments have opened new avenues for capturing and analysing dynamic events with unprecedented temporal and spatial detail, but not without introducing challenges such as optical distortions, motion blur and lighting issues that can affect measurement quality. This review advocates for standardized reporting practices in HS/UHS DIC methodologies to improve reproducibility and reliability across studies, drawing on guidelines from the International Digital Image Correlation Society (iDICs). Through a comprehensive analysis of over 150 articles, this review identifies key advancements in imaging technology and their application in six research domains: material characterization, test development, fracture mechanics, model validation, ballistic and explosive phenomena assessment and measurement uncertainties. Distinctions between two‐dimensional (2D) and stereo‐DIC applications are explored, offering insights into their practical implementation and trade‐offs. Good practices for HS/UHS DIC applications are proposed along with suggestions for future directions for this evolving field, highlighting the indispensable role of technological innovation in expanding the capabilities of optical metrology.

experimental mechanics↗
DOE OSTI2020

Performance of an Isobaric Hybrid Compressed Air Energy Storage System at Minimum Entropy Generation

Efficient, large-scale, and cost-effective energy storage systems provide a means of managing the inherent intermittency of renewable energy sources and drastically increasing their utilization. Compressed air energy storage (CAES) and its derivative architectures have received much attention as a viable solution; however, optimization objectives for these systems have not been thoroughly investigated in the literature. In this work, a hybrid thermal and compressed air energy storage (HT-CAES) system is investigated that mitigates the shortcomings of the otherwise attractive conventional CAES systems and its derivatives—shortcomings such as strict geological locations, low energy densities, and the production of greenhouse gas emissions. The HT-CAES system allows a portion of the available energy to operate a compressor and the remainder to be converted and stored in the form of heat through joule/resistive heating in a high-temperature, sensible, thermal energy storage medium. Internally reversible and irreversible HT-CAES system assumptions were investigated, in addition to regenerative and non-regenerative design configurations. Several system optimization criteria were examined—including maximum energy efficiency, maximum exergy efficiency, maximum work output, and minimum entropy generation—with a focus on whether the latter may lead to conclusive design guidelines in a real system. It is shown that an HT-CAES system designed based on a minimum entropy generation objective may operate at a lower energy and exergy efficiency as well as lower output power than otherwise achievable. Furthermore, optimization objective equivalence is shown to be limited to certain design conditions.

25 ENERGY STORAGE↗
DOE OSTI2020

Analysis of Energy Savings and CO2 Emission Reduction Contribution for Industrial Facilities in USA

Abstract Energy audits can identify energy consumptions, energy costs of the facility and evolve to develop measures to maximize efficiency, optimize supply energy, and eliminate waste. This paper investigates the potential energy savings at 20 different industrial sectors with 152 assessments for various facilities in Wisconsin, USA. On average, eight energy recommendations were suggested and applied in each facility. This paper provides a detailed guideline for each industry in terms of eight different energy categories: heating, ventilation, and air conditioning (HVAC) systems, heat recovery systems, electrical demand management, and utility bills, motors, compressors, waste management, and productivity enhancement, lighting, besides building envelope. In total, the energy savings were as follows: 98 million kWh in the shape of electricity, 561 billion British thermal units (BTUs) gas savings, 44 million gallons water savings, and 2-million-pound solid waste savings. Based on these savings, a 100-thousand-ton reduction in carbon dioxide emissions was obtained.

Energy & Fuels↗
DOE OSTI2022

X-Ray Induced Chemical Reaction Revealed by In Situ X-Ray Diffraction and Scanning X-Ray Microscopy in 15 nm Resolution

The detection sensitivity of synchrotron-based X-ray techniques has been largely improved due to the ever-increasing source brightness, which has significantly advanced ex situ and in situ research for energy materials such as lithium-ion batteries. However, the strong beam–material interaction arising from the high beam flux can substantially modify the material structure. The beam-induced parasitic effect inevitably interferes with the intrinsic material property, making the interpretation of the experimental results difficult and requiring comprehensive assessments. Here, we present a quantitative study of the beam effect on an electrode material Ag 2 VO 2 PO 4 using four different X-ray characterization methods with different radiation dose rates. The material system exhibits interesting and reversible radiation-induced thermal and chemical reactions, further evaluated under electron microscopy to illustrate the underlying mechanism. Further, the work will provide a guideline for using synchrotron X-rays to distinguish the intrinsic behavior from extrinsic structure change of materials induced by X-rays.

36 MATERIALS SCIENCE↗