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

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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A predictive modeling tool for damage analysis and design of hydrogen storage composite pressure vessels

In this study, a predictive modeling tool is developed for damage analysis and design of hydrogen (H 2 ) storage composite pressure vessels. It integrates micromechanics of matrix cracking into a continuum damage mechanics (CDM) description for damage evolution, and three-dimensional (3D) finite element (FE) modeling of the vessel structural response. At the scale of the composite layer (mesoscale), the temperature-dependent stiffness reduction law in terms of the damage variable for transverse matrix cracking is computed using an Eshelby-Mori-Tanaka approach for the initial composite thermoelastic properties and a self-consistent model for the stiffness reduction as a function of the damage variable. While transverse matrix cracking obeying a damage evolution relation can progressively evolve from an initiation to a saturation state, fiber failure is predicted by a micromechanical fiber rupture criterion that accounts for the fiber strength and matrix stress. The implementation of this integrated multiscale modeling model into a 3D FE formulation enables damage analysis and design of H 2 storage composite pressure vessels. The developed tool is illustrated through 3D damage analyses of a cryogenically compressed H 2 storage vessel model subjected to thermomechanical loadings to investigate effects of the helical layer fiber orientation and loading scenario on damage development, vessel integrity and burst pressure.

08 HYDROGEN↗
DOE OSTI2022

Design Tool for Estimating Adsorbent Hydrogen Storage System Characteristics for Light-Duty Fuel Cell Vehicles

This work combines materials development with hydrogen storage technology advancements to address onboard hydrogen storage challenges in light-duty vehicle applications. These systems are comprised of the vehicle requirements design space, balance of plant requirements, storage system components, and materials engineering culminating in the development of an Adsorbent System Design Tool that serves as a preprocessor to the storage system and vehicle-level models created within the Hydrogen Storage Engineering Center of Excellence. Computational and experimental efforts were integrated to evaluate, design, analyze, and scale potential hydrogen storage systems and their supporting components against the Department of Energy 2020 and Ultimate Technical Targets for Hydrogen Storage Systems for Light Duty Vehicles. Ultimately, the Adsorbent System Design Tool was created to assist material developers in assessing initial design parameters that would be required to estimate the performance of the hydrogen storage system once integrated with the full fuel cell system.

08 HYDROGEN↗
DOE OSTI2012

Expansion/De-expansion Tool to Quantify the Accuracy of Prostate Contours

Purpose: Accurate delineation of the prostate gland on computed tomography (CT) remains a persistent challenge and continues to introduce geometric uncertainty into the planning and delivery of external beam radiotherapy. We, therefore, developed an expansion/de-expansion tool to quantify the contour errors and determine the location of the deviations. Methods and Materials: A planning CT scan and magnetic resonance imaging scan were prospectively acquired for 10 patients with prostate cancer. The prostate glands were contoured by 3 independent observers using the CT data sets with instructions to contour the prostate without underestimation but to minimize overestimation. The standard prostate for each patient was defined using magnetic resonance imaging and CT on multiple planes. After registration of the CT and magnetic resonance imaging data sets, the CT-defined prostates were scored for accuracy. The contours were defined as ideal if they were within a 2.5-mm expansion of the standard without underestimation, acceptable if they were within a 5.0-mm expansion and a 2.5-mm de-expansion, and unacceptable if they extended >5.0 mm or underestimated the prostate by >2.5 mm. Results: A total of 636 CT slices were individually analyzed, with the vast majority scored as ideal or acceptable. However, none of the 30 prostate contour sets had all the contours scored as ideal or acceptable. For all 3 observers, the unacceptable contours were more likely from underestimation than overestimation of the prostate. The errors were more common at the base and apex than the mid-gland. Conclusions: The expansion/de-expansion tool allows for directed feedback on the location of contour deviations, as well as the determination of over- or underestimation of the prostate. This metric might help improve the accuracy of prostate contours.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Use of Geriatric Assessment Tools in Selecting Therapies in Women Aged ≥70 Years With Hormone Receptor–Positive Early-Stage Breast Cancer: Preliminary Experience With a Quality Improvement Initiative

Purpose: To develop a multidisciplinary algorithmic approach to management of women aged ≥70 years with clinically staged T1N0 hormone receptor–positive breast cancer, including geriatric assessments predicting life expectancy and the likelihood of functional decline in the near future, in the context of a program-wide quality improvement initiative, to better select patients for therapeutic interventions. Methods and Materials: Two geriatric assessment tools, the Combined Lee-Schonberg Index and the Vulnerable Elderly Scale, were introduced into our clinical workflow to predict long-term mortality and likelihood of functional decline. Scores from these tools, along with patient preferences and clinical features, were incorporated into a preoperative algorithm addressing the use of sentinel lymph node biopsy (SLNB), and a postoperative algorithm addressing the use of adjuvant radiation therapy (RT). Results: The algorithms were approved for use in August 2015. Twenty-four patients were identified by in-clinic screening and have been managed using the algorithms as a guide. Mean patient age was 80 years (range, 71-89 years). Per the preoperative algorithm, consideration of omission of SLNB was an option in 11 of 24 patients (46%), and in total 18 of 24 (75%) opted against SLNB. Per the postsurgical algorithm, consideration of omission of adjuvant RT was an option for 19 of 24 patients (79%), and in total 17 of 24 (71%) opted to forego RT. Conclusion: Incorporation of simple geriatric assessments seems to have had a marked impact on decision making regarding both surgical and adjuvant therapies for women aged ≥70 years with early-stage hormone-positive breast cancer compared with historical patterns, with ≥71% omission of both SLNB and adjuvant RT in patients managed according to an institutional quality improvement initiative.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

PreDSLpmo: A neural network-based prediction tool for functional annotation of lytic polysaccharide monooxygenases

Lytic polysaccharide monooxygenases (LPMOs), a family of copper-dependent oxidative enzymes, boost the degradation of polysaccharides such as cellulose, chitin, and others. While experimental methods are used to validate LPMO function, a computational method that can aid experimental methods and provide fast and accurate classification of sequences into LPMOs and its families would be an important step towards understanding the breadth of contributions these enzymes make in deconstruction of recalcitrant polysaccharides. In this study, we developed a machine learning-based tool called PreDSLpmo that employs two different approaches to functionally classify protein sequences into the major LPMO families (AA9 and AA10). The first approach uses a traditional neural network or multilayer percerptron-based approach, while the second employs bi-directional long short-term memory for sequence classification. Finally, our method shows improvement in predictive power when compared with dbCAN2, an existing HMM-profile-based CAZyme predicting tool, on both validation and independent benchmark set.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗
DOE OSTI2011

A pandemic influenza modeling and visualization tool

The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a modeling and visualization toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A comparative research on bobbin tool and conventional friction stir welding of Al-Mg-Si alloy plates

Highlights: • 6061-T4 Al plates were successfully welded by both BT-FSW and C-FSW processes. • A wide welding parameter window was achieved with bobbin tool. • BT-FSW joints showed good strength similar to that of C-FSW joints. • Proving that an Isothermal Dissolution Layer Theory also apply to BT-FSW - Abstract: In our work, Al-Mg-Si (6061Al -T4) plates of 6 mm thickness were subjected to bobbin tool friction stir welding (BT-FSW) and conventional friction stir welding (C-FSW) for comparison. How the welding process affects the microstructure and mechanical properties was investigated at various rotation rates and welding speeds. The results showed that butt FSW joints with high quality could be produced at the selected parameters. The joint strength rose with enhanced welding speed and was nearly independent of the rotation rate in both the welding processes. The strength of the joints produced with BT-FSW reached the same level as that of the C-FSW. The maximum joint strength of 229 MPa was 93% of the base material (BM), which is superior to the reported results of 60–80% for the T4 condition. The fracture position of most of the joints was in the heat-affected zone (HAZ), which is the lowest hardness zone.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Monaco treatment planning system tools and optimization processes

The Monaco treatment planning system combines Monte Carlo dose calculation accuracy with robust optimization tools to provide high-quality radiotherapy treatment plans for three-dimensional conformal radiotherapy (3D CRT), intensity modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), stereotactic radiosurgery (SRS), and stereotactic body radiotherapy (SBRT). Recent technology advances have allowed for fast calculation speeds, which allow clinicians and patients to benefit from the accuracy of the Monte Carlo algorithm while reducing overall planning time. A collection of biological and physical dose-based planning tools and templates simplify the planning process and allow for consistent results across organizations. At the same time, multicriteria optimization (MCO) ensures critical organs are spared to the greatest possible degree while maintaining target coverage. Monaco encompasses a full suite of treatment modalities, including conventional radiotherapy and particle therapy, and is paving the way for real-time adaptive treatments with developments in magnetic resonance (MR)-guided radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Limitations of traditional tools for beyond design basis external hazard PRA

Probabilistic risk assessment (PRA) is being used increasingly by the nuclear industry for safety during normal operations as well as for the protection against external hazards. Computation of total risk in an external hazard PRA is dependent on hazard assessment, fragility assessment, and systems analysis. A systems analysis for propagation of component fragilities is conducted using event and fault trees. The event and fault trees for an actual power plant can be fairly large in size, which imposes computational challenges. Hence, certain assumptions are employed for computational efficiency. These assumptions typically represent the conditions imposed during the design basis (DB) scenario. The traditional PRA tools based on these assumptions are also widely applied to perform risk assessment in the context of beyond design basis (BDB) scenarios. However, some of these assumptions may not be valid for certain BDB scenarios. In addition, the probability of dependent failures also increases in BDB scenarios due to common cause failures (CCF) which usually results from design modifications, human errors, etc. In this manuscript, a simple and a relatively more complex illustrative examples are used to show the limitation of these assumptions in the numerical quantification of risk for the case of BDB conditions. Case studies with CCF events across multiple fault trees are also presented to illustrate the effect of these assumptions when traditional approach is used in BDB risk assessment. It is shown that the assumptions are valid for the case of DB conditions but may lead to excessively conservative risk estimates in the case of BDB conditions. Finally, a Bayesian network based top-down algorithm is proposed as an alternative tool for accurate numerical quantification of total risk in systems analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Framework development for a SAVY-4000 nuclear material storage container structural integrity surveillance tool

Here, this work presents the preliminary design of an automated surveillance tool to assess the health of SAVY-4000 nuclear material storage containers. This tool is designed by training several machine learning (ML) regression models to predict maximum residual stress in plain dents on the container sidewall. The model is trained on an experimentally validated Finite Element Analysis (FEA) model built in Abaqus FEA. The accuracy of each ML model is compared. The potential for application as well as model shortcomings are assessed. Necessary FEA model improvements are outlined and the various ML models are proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools

We report the overarching hypothesis of this study was that temporal microbial potentiometric sensor (MPS) signal patterns could be used to predict changes in commonly monitored water quality parameters by using artificial intelligence/machine learning tools. To test this hypothesis, the study first examines a proof of concept by correlating between MPS's signals and high algae concentrations in an algal cultivation pond. Then, the study expanded upon these findings and examined if multiple water quality parameters could be predicted in real surface waters, like irrigation canals. Signals generated between the MPS sensors and other water quality sensors maintained by an Arizona utility company, including algae and chlorophyll, were collected in real time at time intervals of 30 min over a period of 9 months. Data from the MPS system and data collected by the utility company were used to train the ML/AI algorithms and compare the predicted with actual water quality parameters and algae concentrations. Based on the composite signal obtained from the MPS, the ML/AI was used to predict the canal surface water's turbidity, conductivity, chlorophyll, and blue-green algae (BGA), dissolved oxygen (DO), and pH, and predicted values were compared to the measured values. Initial testing in the algal cultivation pond revealed a strong linear correlation (R 2 = 0.87) between mixed liquor suspended solids (MLSS) and the MPSs' composite signals. The Normalized Root Mean Square Error (NRMSE) between the predicted values and measured values were <6.5%, except for the DO, which was 10.45%. The results demonstrate the usefulness of MPSs to predict key surface water quality parameters through a single composite signal, when the ML/AI tools are used conjunctively to disaggregate these signal components. The maintenance-free MPS offers a novel and cost-effective approach to monitor numerous water quality parameters at once with relatively high accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Localized Actual Meteorological Year File Creator (LAF): A tool for using locally observed weather data in building energy simulations

The Localized Actual Meteorological Year File Creator (LAF) application provides web-based access to real meteorological data and processes it into a weather file suitable for building energy modeling. Building energy consumption is affected by what is inside the building (such as occupants, appliances, HVAC systems, etc.) and by what is outside: the weather conditions the building is exposed to. However, freely available weather data files are limited to a number of specific locations, usually airports, which are often located away from city centers where buildings are concentrated. The authors have developed a new tool that supports the investigation and quantification of micro-climate conditions on building energy consumption. LAF is built on the Python open-source programming language and has a Graphical User Interface (GUI) that allows users to create custom weather data files for building energy simulations. Many sets of actual meteorological year weather data for long time periods are publicly available online (such as the MesoWest database) for thousands of locations in the US. LAF selects weather data according to user specifications and automatically processes it through an API across multiple weather stations and multiple time periods. The user may easily select a specific location, time frame, and time step that best meets their needs. This article presents a useful tool for energy modelers, building designers and operators to assist with building performance analysis and optimization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

SolarPILOT: A power tower solar field layout and characterization tool

This paper develops and demonstrates a new SolarPower tower Integrated Layout and Optimization Tool (SolarPILOT). The tool uses the analytical flux image Hermite series approximation originally implemented in the DELSOL3 software developed by Sandia National Laboratory in the early 1980s. By applying the analytical model to individual heliostat images rather than large groups or zones of heliostats, SolarPILOT can characterize a wide variety of heliostat field layouts. The individual heliostat modeling approach increases computational expense in comparison with DELSOL3, so SolarPILOT implements a number of improvements to the analytical approximation method to improve model accuracy and computational efficiency. This paper discusses several of these methods, including dynamic heliostat grouping to reduce the expense of intercept factor evaluation, approximation of annual productivity with a subset of time steps throughout the year, polygon clipping to accurately calculate inter-heliostat shadowing and blocking, receiver and tower geometry optimization, and a trigonometric image transformation technique that ensures model accuracy for small heliostats. SolarPILOT also integrates a Monte-Carlo ray tracing engine (SolTrace), providing improved receiver optical modeling capability, a user-friendly front end for geometry definition, and side-by-side validation of the analytical algorithms.

14 SOLAR ENERGY↗
DOE OSTI2025

Damage modeling of power tower receiver tubes using the SRLIFE tool

Concentrating Solar Power (CSP) molten-salt central receivers are subject to high, transient incident flux during daily operation. The resulting creep-fatigue damage impacts the receiver’s reliability and restricts the permissible incident flux distribution for a given receiver. This paper aims to reduce CSP plants’ levelized cost of electricity by developing a methodology to predict lifetime and identifies the primary damage mechanism (creep vs fatigue) for any given fluid temperature and temperature gradient. Results are presented in the form of a damage map that serves as a valuable operation guide and design tool. Damage maps can be used to reduce maintenance costs by improving reliability and reduce receiver capital costs by better utilizing the receiver area. FEA simulation and damage modeling of tubes subject to asymmetrical flux conditions is performed in the open-source receiver design tool srlife. Parametric studies are performed over a range of inner tube temperatures and thermal gradients for A230, 316H, 740H, A282, A617, and 800H high temperature alloys. Damage maps are presented for each alloy. A parametric, FEA-based methodology is presented for comparison of fatigue-creep ratios and prediction of tube lifetime based on the critical thermal operating conditions. Fatigue is found to be negligible compared to creep for almost every case. Here, this finding suggests that fatigue effects associated with cloud events are insignificant compared to creep at these high temperature operating conditions. Additionally, lifetime predictions identify thermal conditions where small changes in operating conditions can result in large changes in predicted lifetime.

14 SOLAR ENERGY↗
DOE OSTI2016

Investigation of the therapeutic potential of N-acetyl cysteine and the tools used to define nigrostriatal degeneration in vivo

The glutathione precursor N-acetyl-L-cysteine (NAC) is currently being tested on Parkinson's patients for its neuroprotective properties. Our studies have shown that NAC can elicit protection in glutathione-independent manners in vitro. Thus, the goal of the present study was to establish an animal model of NAC-mediated protection in which to dissect the underlying mechanism. Mice were infused intrastriatally with the oxidative neurotoxicant 6-hydroxydopamine (6-OHDA; 4 μg) and administered NAC intraperitoneally (100 mg/kg). NAC-treated animals exhibited higher levels of the dopaminergic terminal marker tyrosine hydroxylase (TH) in the striatum 10d after 6-OHDA. As TH expression is subject to stress-induced modulation, we infused the tracer FluoroGold into the striatum to retrogradely label nigrostriatal projection neurons. As expected, nigral FluoroGold staining and cell counts of FluoroGold{sup +} profiles were both more sensitive measures of nigrostriatal degeneration than measurements relying on TH alone. However, NAC failed to protect dopaminergic neurons 3 weeks following 6-OHDA, an effect verified by four measures: striatal TH levels, nigral TH levels, nigral TH{sup +} cell counts, and nigral FluoroGold levels. Some degree of mild toxicity of FluoroGold and NAC was evident, suggesting that caution must be exercised when relying on FluoroGold as a neuron-counting tool and when designing experiments with long-term delivery of NAC—such as clinical trials on patients with chronic disorders. Finally, the strengths and limitations of the tools used to define nigrostriatal degeneration are discussed. - Highlights: • N-acetyl cysteine (NAC) was injected into animals infused with the toxicant 6-OHDA. • Retrograde tracing with FluoroGold was used to define nigrostriatal cell loss. • Infrared Odyssey imaging and cell counts were used to screen for nigral cell loss. • NAC protected transiently against 6-OHDA but this effect waned over time. • Mildly toxic effects of chronic NAC delivery may influence future clinical trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Development and validation of the cavitation-induced erosion risk assessment tool

This work presents the development of a cavitation-induced erosion risk assessment (CIERA) tool that links multiphase flow simulation predictions with the progress towards material erosion. To develop a robust erosion modeling tool, the cavitation and erosion predictions for pressurized diesel fuel flow within a channel geometry were validated over a range of Reynolds and cavitation number conditions in two different aluminum channel geometries, one featuring a rounded inlet corner and the other with a sharp inlet corner. The multiphase flow development within the channel was modeled using a compressible mixture model, where phase change was represented with the homogeneous relaxation model and the turbulent flow evolution was modeled using a dynamic structure approach for Large Eddy Simulations. To improve representation of the incubation period before material rupture over existing approaches, a physics-based metric was derived based on the cumulative energy absorbed by the solid material from repeated hydrodynamic impacts. When the average peak pressure was related to the incubation period, the incubation period and its sensitivity to changes in flow conditions were found to be overpredicted. In contrast, predictions from CIERA provided a more accurate means to qualitatively and quantitatively predict the influence of flow conditions on the incubation period before material erosion. When the predicted stored energy was related to the solid material properties to estimate the incubation period, multiphase flow simulations demonstrated accurate representation of the sensitivity of erosion severity to changes in flow conditions. The use of CIERA led to quantitative agreement of the predicted incubation period within 5% of the experimentally measured incubation period.

42 ENGINEERING↗
DOE OSTI2014

Effective dialogue: Enhanced public engagement as a legitimising tool for municipal waste management decision-making

Highlights: • A review of public engagement in waste management decision-making is undertaken. • Enhanced public engagement is explored as a means to legitimise waste decisions. • Analytical–deliberative processes are explored as a tool for effective dialogue. • Considerations for integrating public values with technical analysis are outlined. • Insights into the design of appropriate public engagement processes are provided. - Abstract: The complexity of municipal waste management decision-making has increased in recent years, accompanied by growing scrutiny from stakeholders, including local communities. This complexity reflects a socio-technical framing of the risks and social impacts associated with selecting technologies and sites for waste treatment and disposal facilities. Consequently there is growing pressure on local authorities for stakeholders (including communities) to be given an early opportunity to shape local waste policy in order to encourage swift planning, development and acceptance of the technologies needed to meet statutory targets to divert waste from landfill. This paper presents findings from a research project that explored the use of analytical–deliberative processes as a legitimising tool for waste management decision-making. Adopting a mixed methods approach, the study revealed that communicating the practical benefits of more inclusive forms of engagement is proving difficult even though planning and policy delays are hindering development and implementation of waste management infrastructure. Adopting analytical–deliberative processes at a more strategic level will require local authorities and practitioners to demonstrate how expert-citizen deliberations may foster progress in resolving controversial issues, through change in individuals, communities and institutions. The findings suggest that a significant shift in culture will be necessary for local authorities to realise the potential of more inclusive decision processes. This calls for political actors and civic society to collaborate in institutionalising public involvement in both strategic and local planning structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗