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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 55 records · Page 3

Review—Thermal Safety Management in Li-Ion Batteries: Current Issues and Perspectives

Approaches for thermal management of lithium-ion (Li-ion) batteries do not always keep pace with advances in energy storage and power delivering capabilities. Root-cause analysis and empirical evidence indicate that thermal runaway (TR) in cells and cell-to-cell thermal propagation are due to adverse changes in physical and chemical characteristics internal to the cell. However, industry widely uses battery management systems (BMS) originally designed for aqueous-based batteries to manage Li-ion batteries. Even the "best" BMS that monitor both voltage and outside-surface temperature of each cell are not capable of preventing TR or TR propagation, because voltage and surface-mounted temperature sensors do not track fast-emerging adverse events inside a cell. Most BMS typically include a few thermistors mounted on select cells to monitor their surface temperature. Technology to track intra-cell changes that are TR precursors is becoming available. Simultaneously, the complex pathways resulting in cell-to-cell TR propagation are being successfully modelled and mapped. Innovative solutions to prevent TR and thermal propagation are being advanced. These include modern BMS for rapid monitoring the internal health of each individual cell and physical as well as chemical methods to reduce the deleterious effects of rapid cell-to-cell heat and material transport in case of TR.

25 ENERGY STORAGE↗

A framework for inferring and analyzing pharmacotherapy treatment patterns

Background: To discover pharmacotherapy prescription patterns and their statistical associations with outcomes through a clinical pathway inference framework applied to real-world data. Methods: We apply machine learning steps in our framework using a 2006 to 2020 cohort of veterans with major depressive disorder (MDD). Outpatient antidepressant pharmacy fills, dispensed inpatient antidepressant medications, emergency department visits, self-harm, and all-cause mortality data were extracted from the Department of Veterans Affairs Corporate Data Warehouse. Results: Our MDD cohort consisted of 252,179 individuals. During the study period there were 98,417 emergency department visits, 1,016 cases of self-harm, and 1,507 deaths from all causes. The top ten prescription patterns accounted for 69.3% of the data for individuals starting antidepressants at the fluoxetine equivalent of 20-39 mg. Additionally, we found associations between outcomes and dosage change. Conclusions: For 252,179 Veterans who served in Iraq and Afghanistan with subsequent MDD noted in their electronic medical records, we documented and described the major pharmacotherapy prescription patterns implemented by Veterans Health Administration providers. Ten patterns accounted for almost 70% of the data. Associations between antidepressant usage and outcomes in observational data may be confounded. The low numbers of adverse events, especially those associated with all-cause mortality, make our calculations imprecise. Furthermore, our outcomes are also indications for both disease and treatment. Despite these limitations, we demonstrate the usefulness of our framework in providing operational insight into clinical practice, and our results underscore the need for increased monitoring during critical points of treatment.

60 APPLIED LIFE SCIENCES↗

NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study

Abstract Background Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. Methods A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. Results Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53–0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47–0.56), invasive ventilation (OR: 0.59 95% CI: 0.55–0.64), AKI (OR: 0.67 95% CI: 0.63–0.72), or ECMO (OR: 0.51 95% CI: 0.36–0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. Conclusions Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

60 APPLIED LIFE SCIENCES↗

Xanthohumol microbiome and signature in adults with Crohn’s disease (the XMaS trial): a protocol for a phase II triple-masked, placebo-controlled clinical trial

Xanthohumol (XN), a bioactive flavonoid from Humulus lupulus with anti-inflammatory properties, has potential benefits for patients with Crohn’s disease (CD), a type of inflammatory bowel disease. We recently completed and published results of a placebo-controlled phase I clinical trial demonstrating the safety and tolerability of 24 mg XN daily for 8 weeks. The present study aims to evaluate the safety and tolerability of the same dose of XN adults with clinically active CD in a placebo-controlled phase II clinical trial. Additional aims will assess the impact of XN on inflammatory biomarkers, platelet function, CD clinical activity, and stool microbial composition. The metabolism of XN will also be evaluated. This article provides a model protocol for consideration in investigations of XN or other natural products in disease states. A triple-masked, randomized, placebo-controlled trial will be conducted in adults with clinically active CD. Participants (n ≤ 32) will be randomized to either 24 mg encapsulated XN per day or placebo and followed for 8 weeks. Throughout the trial, participants will be queried for adverse events. Biomarkers of clinical safety, blood and stool markers of inflammation, platelet function, Crohn’s Disease Activity Index score, stool microbial composition, and XN metabolite profiles in blood, urine, and stool will be assessed every 2 weeks. We describe the protocol for a phase II clinical trial that evaluates the safety and tolerability of XN in adults with active CD, as well as evaluate metabolism and mechanisms that are relevant to CD and other diseases with underlying inflammation and/or gut permeability. The effects of XN on inflammatory biomarkers, platelet function, the microbiota, and multi-omics biomarkers measured in this phase II trial of adults with CD will be compared to the effects of XN in healthy adults in our previous phase I trial. The results of the study will advance the evidence guiding the use of XN in patients with CD.

60 APPLIED LIFE SCIENCES↗

CpG ODN D35 improves the response to abbreviated low-dose pentavalent antimonial treatment in non-human primate model of cutaneous leishmaniasis

Cutaneous leishmaniasis (CL) affects the lives of 0.7–1 million people every year causing lesions that take months to heal. These lesions can result in disfiguring scars with psychological, social and economic consequences. Antimonials are the first line of therapy for CL, however the treatment is lengthy and linked to significant toxicities; further, its efficacy is variable and resistant parasites are emerging. Shorter or lower dose antimonial treatment regimens, which would decrease the risk of adverse events and improve patient compliance, have shown reduced efficacy and further increase the risk emergence of antimonial-resistant strains. The progression of lesions in CL is partly determined by the immune response it elicits, and previous studies showed that administration of immunomodulatory type D CpG ODNs, magnifies the immune response to Leishmania and reduces lesion severity in nonhuman primates (NHP) challenged with Leishmania major or Leishmania amazonensis. Here we explored whether the addition of a single dose of immunomodulating CpG ODN D35 augments the efficacy of a short-course, low-dose pentavalent antimonial treatment regimen. Results show that macaques treated with D35 plus 5mg/kg sodium stibogluconate (SbV ) for 10 days had smaller lesions and reduced time to re-epithelization after infection with Leishmania major. No toxicities were evident during the studies, even at doses of D35 10 times higher than those used in treatment. Critically, pentavalent antimonial treatment did not modify the ability of D35 to induce type I IFNs. The findings support the efficacy of D35 as adjuvant therapy for shorter, low dose pentavalent antimonial treatment.

59 BASIC BIOLOGICAL SCIENCES↗

New machine protection system at the Spallation Neutron Source – design process and performance analysis

A New Machine Protection System (MPS) at the Spallation Neutron Source (SNS) was developed and implemented on µTCA-based hardware platforms. The system monitors more than 2500 field inputs and shuts off the beam within 10 µs if adverse events occur. We will present system level design process of various firmware and software components as well as the system integration into EPICS environment. The performance analysis of the MPS after two SNS run cycles will also be presented.

Bobrek, Miljko [ORNL] (ORCID:0000000332763451)↗

Stewardship Considerations for Nevada FFACO Corrective Action Units Closed through the EM NV Soils Activity based on Monitoring of Radionuclide Transport

This report summarizes the EM NV/DRI work with the intent of conveying this information to the long-term land managers who will assume responsibility as EM NV completes its environmental restoration mission. A brief description of each of the six evaluated Soils Activity sites is provided, which is followed by a discussion of the findings regarding radionuclide transport learned at the sites. The implications of these findings are examined for site management, routine monitoring, and monitoring during potentially adverse events. Possible mitigation actions are also identified. The appendices provide a more detailed examination of the conditions under which radionuclide transport occurs at these sites.

54 ENVIRONMENTAL SCIENCES↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Current and Future Work on Wound Contamination by Alpha Emitters at Los Alamos [Slides]

Our team calculated ‘clinical decision levels’ at which treatment may be warranted (i.e., bioassay and wound measurements which correspond to specific dose thresholds). The actual risk to the patient corresponding to this dose threshold is uncertain – the CED may not tell the whole story. We recently reviewed LANL medical records to characterize adverse events associated with treatment. Future work should include medical records from other institutions and a review and analysis of data to quantify benefit of treatment with a focus on the question, "What factors predict whether treatment will be beneficial?"

61 RADIATION PROTECTION AND DOSIMETRY↗

Best Practices for Grid Communications

As the grid evolves, the communications architecture will need to evolve with it. That architecture affords a structured means by which the evolving complexities of the modern electric grid can be managed. This document provides best practices that can be implemented in the grid of today and evolve towards the grid and grid architecture of the future. The evolving grid and its control communications increasingly rely on commercial communications providers and a variety of technologies, from wireless (e.g., 5G, microwave, Wi-Fi) to wireline (fiber, copper) to radio communications (P25, other repeater-based systems), and all these communications systems rely on electric power. A reliable and resilient grid must account for this complex set of interdependencies in its planning activities, especially those involving restoration and recovery. The participation of all relevant parties in both planning and exercising of plans can prevent unexpected conditions that impede the reliable operation and recovery of the grid. Best practices for grid communications include using a Network Management System to document the operational state, define and monitor baselines, detect changes, and accelerate response to abnormalities. If transitioning from SONET to IP/packet-based systems, translating grid requirements into communications requirements for latency, bandwidth and throughput, IP packet delay variation, packet loss, and availability should inform and drive technology planning and selection as well as that communication system’s Quality of Service (QoS) policies and Service Level Agreements (SLAs). Secure and reliable timing is another key component of a reliable and resilient grid that can operate through adverse events. A trusted internal NTP configuration, an integrated and diverse timing delivery system, optimizing the timing architecture based on the transport technologies of the communications system, and using established standards can deliver the level of timing accuracy required by a range of time-sensitive power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The MHC Associated Peptide Proteomics assay is a useful tool for the non-clinical assessment of immunogenicity

The propensity of therapeutic proteins to elicit an immune response, poses a significant challenge in clinical development and safety of the patients. Assessment of immunogenicity is crucial to predict potential adverse events and design safer biologics. In this study, we employed MHC Associated Peptide Proteomics (MAPPS) to comprehensively evaluate the immunogenic potential of re-engineered variants of immunogenic FVIIa analog (Vatreptacog Alfa). Our finding revealed the correlation between the protein sequence affinity for MHCII and the number of peptides identified in a MAPPS assay and this further correlates with the reduced T-cell responses. Moreover, MAPPS enable the identification of “relevant” T cell epitopes and may contribute to the development of biologics with lower immunogenic potential.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of intracoronary hemodynamics identifies perturbations in vorticity

Coronary artery disease (CAD) is highly prevalent and associated with adverse events. Challenges have emerged in the treatment of intermediate coronary artery stenoses. These lesions are often interrogated with fractional flow reserve (FFR) testing to determine if a stenosis is likely to be causative for ischemia in a cardiac territory. This invasive test requires insertion of a pressure wire into a coronary vessel. Recently computational fluid dynamics (CFD) has been used to noninvasively assess fractional flow reserve in vessels reconstructed from medical imaging data. However, many of these simulations are unable to provide additional information about intravascular hemodynamics, including velocity, endothelial shear stress (ESS), and vorticity. We hypothesized that vorticity, which has demonstrated utility in the assessment of ventricular and aortic diseases, would also be an important hemodynamic factor in CAD. Three-dimensional (3D), patient-specific coronary artery geometries that included all vessels >1 mm in diameter were created from angiography data obtained from 10 patients who underwent diagnostic angiography and FFR testing (n = 9). A massively parallel CFD solver (HARVEY) was used to calculate coronary hemodynamic parameters including pressure, velocity, ESS, and vorticity. These simulations were validated by comparing velocity flow fields from simulation to both velocities derived from in vitro particle image velocimetry and to invasively acquired pressure wire-based data from clinical testing. There was strong agreement between findings from CFD simulations and particle image velocimetry experimental testing (p < 0.01). CFD-FFR was also highly correlated with invasively measured FFR (ρ = 0.77, p = 0.01) with an average error of 5.9 ± 0.1%. CFD-FFR also had a strong inverse correlation with the vorticity (ρ = -0.86, p = 0.001). Simulations to determine the effect of the coronary stenosis on intravascular hemodynamics demonstrated significant differences in velocity and vorticity (both p < 0.05). Further evaluation of an angiographically normal appearing non-FFR coronary vessel in patients with CAD also demonstrated differences in vorticity when compared with FFR vessels (p < 0.05). The use of highly accurate 3D CFD-derived intravascular hemodynamics provides additional information beyond pressure measurements that can be used to calculate FFR. Vorticity is one parameter that is modified by a coronary stenosis and appears to be abnormal in angiographically normal vessels in patients with CAD, highlighting a possible use-case in preventative screening for early coronary disease.

59 BASIC BIOLOGICAL SCIENCES↗

Tracing and Forecasting Metabolic Indices of Cancer Patients Using Patient-Specific Deep Learning Models

We develop a patient-specific dynamical system model from the time series data of the cancer patient’s metabolic panel taken during the period of cancer treatment and recovery. The model consists of a pair of stacked long short-term memory (LSTM) recurrent neural networks and a fully connected neural network in each unit. It is intended to be used by physicians to trace back and look forward at the patient’s metabolic indices, to identify potential adverse events, and to make short-term predictions. When the model is used in making short-term predictions, the relative error in every index is less than 10% in the L ∞ norm and less than 6.3% in the L 1 norm in the validation process. Once a master model is built, the patient-specific model can be calibrated through transfer learning. As an example, we obtain patient-specific models for four more cancer patients through transfer learning, which all exhibit reduced training time and a comparable level of accuracy. This study demonstrates that this modeling approach is reliable and can deliver clinically acceptable physiological models for tracking and forecasting patients’ metabolic indices.

60 APPLIED LIFE SCIENCES↗

T Cells Contribute to Pathological Responses in the Non-Targeted Rat Heart following Irradiation of the Kidneys

Heart disease is a significant adverse event caused by radiotherapy for some cancers. Identifying the origins of radiogenic heart disease will allow therapies to be developed. Previous studies showed non-targeted effects manifest as fibrosis in the non-irradiated heart after 120 days following targeted X-irradiation of the kidneys with 10 Gy in WAG/RijCmcr rats. To demonstrate the involvement of T cells in driving pathophysiological responses in the out-of-field heart, and to characterize the timing of immune cell engagement, we created and validated a T cell knock downrat on the WAG genetic backgrou nd. Irradiation of the kidneys with 10 Gy of X-rays in wild-type rats resulted in infiltration of T cells, natural killer cells, and macrophages after 120 days, and none of these after 40 days, suggesting immune cell engagement is a late response. The radiation nephropathy and cardiac fibrosis that resulted in these animals after 120 days was significantly decreased in irradiated T cell depleted rats. We conclude that T cells function as an effector cell in communicating signals from the irradiated kidneys which cause pathologic remodeling of non-targeted heart.

60 APPLIED LIFE SCIENCES↗

A Two-Step Restoration Scheme with DER Controllability for Resilient Distribution Systems

Modern distribution systems have increasing integration of distributed energy resources (DERs). A large number of distribution system DERs are interfaced through a power electronic converter. During grid contingency scenarios these resources have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid's restoration after an adverse event and hence enhancing resilience. In distribution systems, system restoration is an important problem, especially in face of high-impact low-frequency events. This paper proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in DERs for mitigating voltage problems. Simulation studies are performed on the IEEE-123 node feeder system to demonstrate the effectiveness of the proposed method for various cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimized Dispatch of Distributed Energy Resources for Resiliency and Power Quality Improvements at the Grid-Edge

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

Chowdhury, Prithwiraj Roy↗

Task 5: Developing a Tool to Quantify Liability of Geologic Carbon Storage

This talk provides an overview of work being done on NRAP Phase 3 Task 5. Task 5 involves the liability or cost of responding to potential adverse events. The focus of Task 5 is on the cost of responding to potential leakage of CO2 and brine out of the storage formation or induced seismic incidents.

Morgan, David↗