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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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Assessing Impact of Aerosol Intercontinental Transport on Regional Air Quality and Climate: What Satellites Can Help
Mounting evidence for intercontinental transport of aerosols suggests that aerosols from a region could significantly affect climate and air quality in downwind regions and continents. Current assessment of these impacts for the most part has been based on global model simulations that show large variability. The aerosol intercontinental transport and its influence on air quality and climate involve many processes at local, regional, and intercontinental scales. There is a pressing need to establish modeling systems that bridge the wide range of scales. The modeling systems need to be evaluated and constrained by observations, including satellite measurements. Columnar loadings of dust and combustion aerosols can be derived from the MODIS and MISR measurements of total aerosol optical depth and particle size and shape information. Characteristic transport heights of dust and combustion aerosols can be determined from the CALIPSO lidar and AIRS measurements. CALIPSO liar and OMI UV technique also have a unique capability of detecting aerosols above clouds, which could offer some insights into aerosol lofting processes and the importance of above-cloud transport pathway. In this presentation, I will discuss our efforts of integrating these satellite measurements and models to assess the significance of intercontinental transport of dust and combustion aerosols on regional air quality and climate.
Preliminary Assessment of a Distributed Electric Propulsion System for the SUSAN Electrofan
The SUSAN Electrofan is a new hybrid electric large regional jet aircraft concept being studied by NASA that leverages advanced propulsion system technologies such as distributed electric propulsion (DEP) and boundary-layer ingestion (BLI) to reduce fuel consumption and emissions. In order to evaluate the individual benefits of these technologies toward the SUSAN Electrofan’s wing-mounted propulsion systems, three configurations are proposed. The first consists of two underwing pylon-mounted podded propulsors and serves as a baseline, while the second features an underwing pylon-mounted DEP concept with 16 ducted fans in a mail-slot nacelle. The third and final configuration mounts the mail-slot nacelle directly onto the pressure side of the wing to also take advantage of BLI. This paper presents preliminary investigations into the design and performance of the first two propulsion system configurations. This begins with an initial propulsor and mail-slot design where the aeropropulsive design space is explored, and adverse effects are addressed through iterative geometry modifications. The propulsion system configurations are then installed onto a wing–body model to account for integration effects and assess the relative aerodynamic and shaft power performance of each concept. Results indicate the potential benefits of DEP, which come from significant reductions in total drag, provided by operation at much lower propulsor fan pressure ratios.
Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land-Atmosphere Coupling
The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from ‘off-the-shelf’ products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high resolution land surface model and in-situ soil moisture estimates. Case studies are analyzed using the local land-atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land vs. atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.
Exploring the future energy-mobility nexus: The transportation energy & mobility pathway options (TEMPO) model
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Cross-Cutting Computational Modeling Project: Integrative Modeling Approach
A wide range of computational models and analyses have been applied to spaceflight risk assessment and countermeasure development. The benefits of using computational modeling to enhance Human Research Program (HRP) goals include the ability to mathematically represent physiological systems, integrate multiple, discrete experimental measures, span multiple temporal and spatial scales, determine important factors within the system and provide estimates of unmeasurable quantities. In the area of application, computational models provide a means of developing simulations to test hypotheses, determining key factors of the system to aid experimental design and bridging gaps in sparse data by mathematically simulating large populations. Specifically, computational models and their supporting analysis tools have the proven potential to integrate analyses of risk factors to enhance mission planning and preparation capabilities and to inform spacecraft design and countermeasure development. Appropriately applied, computational models may allow intelligent, unbiased physiological parameter assessment to enable hypothesis testing and model based design of experiments. HRP recently formed the Computational Modeling Project (CMP), managed out of Glenn Research Center, as a cross-cutting activity aimed at leveraging the growing power and acceptance of computational modeling in informing clinical, physiological, and biological studies. This presentation will provide an overview of the challenges and opportunities in implementing various forms of computational models in support of the HRPs path to risk reduction.
A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation
Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.
Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science
This article is about the state of ICON principles Goldman et al. (2021), https://doi.org/10.1029/2021EO153180 in natural hazards and a discussion on the opportunities and challenges of adopting them. Natural hazards pose risks to society, infrastructure, and the environment. Hazard interactions and their cascading phenomena in space and time can further intensify the impacts. Natural hazards’ risks are expected to increase in the future due to environmental, demographic, and socioeconomic changes. It is important to quantify and effectively communicate risks to inform the design and implementation of risk mitigation and adaptation strategies. Multihazard multisector risk management poses several nontrivial challenges, including: (a) integrated risk assessment, (b) Earth system data-model fusion, (c) uncertainty quantification and communication, and (d) crossing traditional disciplinary boundaries. Here, we review these challenges, highlight current research and operational endeavors, and underscore diverse research opportunities. We emphasize the need for integrated approaches, coordinated processes, open science, and networked efforts (ICON) for multihazard multisector risk management.
Automatic Generation of Event Trees and Fault Trees: A Model-Based Approach
In the past few decades, the increasing complexity of modern engineering systems has been driven by the integration of a large number of components whose operations may involve many disciplines (e.g., thermal hydraulics, plant operations, cybersecurity). Most computational tools used by industry and regulators for system safety and reliability assessments are still based on the traditional fault tree (FT) and event tree (ET) approach, which may not be able to capture complex interactions among system constituents. The use of simulation tools has widely increased in the past few decades to improve the fidelity of the reliability and safety analyses. However, the direct use of simulation tools as part of dynamic probabilistic risk assessment (DPRA) methods is not getting traction since (1) modeling the whole system under consideration with DPRA methods may be computationally expensive and unnecessary, and (2) the manual integration of DPRA models into existing state-of-practice probabilistic risk assessment models (i.e., based on FTs and ETs) can be time consuming and prone to errors. Here, in this paper we propose a procedure to overcome this limitation by presenting several algorithms designed to automatically construct subsystem ETs and FTs from DPRA methods for integration into an existing ET/FT system model.
Uncertainty Analysis Framework for the Hospital Resource Supply Model for Covid-19
In March and April of 2020 there was widespread concern about availability of medical resources required to treat Covid-19 patients who become seriously ill. A simulation model of supply management was developed to aid understanding of how to best manage available supplies and channel new production. Forecasted demands for critical therapeutic resources have tremendous uncertainty, largely due to uncertainties about the number and timing of patient arrivals. It is therefore essential to evaluate any process for managing supplies in view of this uncertainty. To support such evaluations, we developed a modeling framework that would allow an integrated assessment in the context of uncertainty quantification. At the time of writing there has been no need to execute this framework because adaptations of the medical system have been able to respond effectively to the outbreak. This report documents the framework and its implemented components should need later arise for its application.
International Space Station Power System Model Validated
System Power Analysis for Capability Evaluation (SPACE) is a computer model of the International Space Station's (ISS) Electric Power System (EPS) developed at the NASA Glenn Research Center. This uniquely integrated, detailed model can predict EPS capability, assess EPS performance during a given mission with a specified load demand, conduct what-if studies, and support on-orbit anomaly resolution.
Simple Tool for Aircraft Noise-Reduction Route Design
The design of arrival and departure routes from an airport has to balance the conflicting requirements of fuel efficiency, airport capacity utilization and community emission and noise considerations. The commonly used tools for aircraft noise assessment are the FAA’s Integrated Noise Model (INM) and Aviation Environmental Design Tool (AEDT). These tools are suitable to generate precise noise contours. However, they are harder to use with other tools for route design optimization involving evaluation of a large number of aircraft trajectories. A simplified aircraft noise computation tool, named AIRNOISE, is developed for preliminary aircraft noise-reduction route design in this paper. AIRNOISE computes aircraft noise based on the same SAE-AIR-1845 procedures used by INM and AEDT. AIRNOISE does not consider components related to terrain and atmosphere adjustments. As a result, it is not only computationally efficient but also flexible to use for customized aircraft profiles. The aircraft noise results are compared with the FAA’s AEDT2b and show that the level of accuracy achieved by AIRNOISE can be used to reduce the number of route design options to a small number from a large pool for subsequent accurate analysis by INM.
INTEGRATION OF FLEX EQUIPMENT AND OPERATOR ACTIONS IN PLANT FORCE-ON-FORCE MODELS WITH DYNAMIC RISK ASSESSMENT
The overall operation and maintenance cost to protect nuclear power plants accounts for approximately 7% of the total cost of power generation, with labor accounting for half of this cost. In the current research, from interaction with utilities and other stakeholders, it was determined that physical security forces account for nearly 20% of the entire workforce at several nuclear power plants. Labor costs continue to rise in the U.S., so any measures to reduce the cost of operating a nuclear power plant will need to include a reduction in labor. The physical security pathway within the DOE’s Light Water Reactor Sustainability program aims to lower the cost of physical security through directed research into modeling and simulation, application of advanced sensors or deployment of advanced weapons. This report presents a modeling and simulation framework for integrating Diverse and Flexible Mitigation Capability (FLEX) portable equipment performance with Force on Force models of a plant’s physical security posture. The generic framework is described in detail, followed by a case study of modeling an adversarial attack aimed at causing a radiological release by sabotaging the plant’s power supply and its ultimate heat sink capabilities at a hypothetical nuclear power plant. Two different FLEX deployment strategies, series and parallel, are modeled with distinct timelines. The results of the adversarial attack modeled in a commercial Force on Force tool are integrated with the FLEX deployment model in INL’s dynamic modeling tool EMRALD. Monte Carlo simulation is used to model the distribution of the timeline in FLEX deployment strategies. The results demonstrate that, even in the extreme case of a successful adversarial attack, deployment of FLEX equipment can result in a significantly high likelihood of preventing radiological release. The modeling and simulation framework integrating FLEX equipment with Force on Force models enables the nuclear power plants to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.
A novel methodology to integrate outcomes regarding perioperative pain experience into a composite score: Prediction model development and validation
Abstract Background An integrated score that globally assesses perioperative pain experience and rationally weights each component has not yet been developed. Methods A development dataset specific to adult Chinese patients undergoing orthopaedic surgery was obtained from PAIN OUT (1985 qualified patients of 2244). A more recent validation dataset obeying the same conditions was obtained from the Chinese Anaesthesia Shared‐database Platform (1004 qualified patients of 1032). Outcomes were assessed using the International Pain Outcomes Questionnaire (IPO‐Q), which comprises key patient‐level outcomes of perioperative pain management, including pain experience and perceptions of care. Using principal component analysis and regression models, a composite score (CS) was inferred to integrate pain experience. The discrimination of the CS for dissatisfaction and desire for more pain treatment was compared with that of the worst pain score. Results A CS was developed from the 12 items of the IPO‐Q regarding pain experience. The weight for calculating the CS was worst pain 11, least pain 17, time spent in severe pain 11, interference with activity in bed 9, interference with breathing deeply or coughing 10, interference with sleep 9, anxiety 12, helplessness 12, nausea 0, drowsiness 2, itch 5 and dizziness 2. In external validation, the CS indicated superior discrimination to the worst pain in predicting dissatisfaction ( p < 0.001) and desire for more pain treatment ( p < 0.001). Conclusions This study introduced a methodology to integrate outcomes regarding perioperative pain experience into a CS, which was based on the weight of each item. Significance This novel methodology sheds additional light on the riveting issue of carefully integrating several measures into a composite endpoint, which may be useful for quality improvement purposes when addressing the impact of a change in clinical practice.
Simplified Model for iLIDS IDD
The NASA Docking System (NDS) Project has provided simplified volumetric models for use by potential hosts vehicles to assess vehicle integration. It should be noted that the JSC-65795 NDS Interface Definition Document (IDD) takes precedence over this simplified model. The simplified model serves as a graphical representation only. It is therefore important to state that dimensions and tolerances are to be taken from the IDD document and supersede any measurements derived from the provided simplified model geometry.
Energy Northwest — Advanced Grid Interactive Load Efficiency (AGILE) : A Techno-economic Assessment
The Advanced Grid Interactive Load Efficiency project team, led by Energy Northwest, was awarded funding as part of the fourth round of the Clean Energy Fund program to investigate, co-create, and complete a preliminary design for grid-interactive efficient buildings (GEBs) for a number of schools served by Grays Harbor PUD. The project team has evaluated different combinations of systems at selected school buildings and the potential to respond to grid and customer needs, and develop a preliminary system technical design, including specifying desired GEB technology options, determining communication and electrical interface requirements, assessing control software sensor requirements, and interfacing with building management systems. PNNL led the techno-economic assessment efforts, leveraging its advanced modeling and analytical methods and tools developed for building-to-grid integration. This report documents the economic assessment for different GEB design options, encompassing an in-depth examination of use cases and value propositions, assumptions and inputs, models, methods, case studies, as well as key findings.
OECD/NEA MPCMIV Benchmark - Preliminary fuel performance results
The on-going OECD/NEA Multi-physics Pellet Cladding Mechanical Interaction Validation (MPCMIV) benchmark aims to provide guidance on multi-physics validation through the modelling of two cold ramps. In this paper, the first results for the base irradiation of the father rod and fuel rodlet (refabricated from the father rod), and the first cold ramp are presented. The base irradiation consists of 3 years of irradiation in the Forsmark-2 reactor. The cold ramp encompasses a steady-state pre-ramp period of less than one hour at a low constant linear heat rate (LHR) followed by a ramp test (< 1 min) with a much higher maximal LHR. The base irradiation is modelled using the fuel performance codes FRAPCON and FAST, while the cold ramp modeling is using the fuel performance code FRAPTRAN. Several missing parameters for FRAPCON/FAST base irradiation models have been selected using multiple references such as the OECD/NEA light water reactor Uncertainty Analysis in Modelling (UAM) benchmark specifications and the FRAPCON Integral Assessment report. The obtained results for the base irradiation such as the cladding outer diameter show reasonable agreement with the experimental measurements. The results for the cold ramp show larger differences with the experimental measurements (e.g., cladding axial elongation). However, such differences have been observed as well in other studies involving pellet cladding mechanical interaction analyses and are attributed to the fuel performance modelling assumptions and to the tuned modelling parameters that were not covered by the specifications. Uncertainty and sensitivity analysis might allow a better quantification of these missing parameters. (authors)
Framework for the Parametric System Modeling of Space Exploration Architectures
This paper presents a methodology for performing architecture definition and assessment prior to, or during, program formulation that utilizes a centralized, integrated architecture modeling framework operated by a small, core team of general space architects. This framework, known as the Exploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), enables: 1) a significantly larger fraction of an architecture trade space to be assessed in a given study timeframe; and 2) the complex element-to-element and element-to-system relationships to be quantitatively explored earlier in the design process. Discussion of the methodology advantages and disadvantages with respect to the distributed study team approach typically used within NASA to perform architecture studies is presented along with an overview of EXAMINE s functional components and tools. An example Mars transportation system architecture model is used to demonstrate EXAMINE s capabilities in this paper. However, the framework is generally applicable for exploration architecture modeling with destinations to any celestial body in the solar system.