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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 91 records · Page 5

Blueprinting Electrified Transit System Implementation

To achieve a more affordable and reliable transportation system, we need to smartly upgrade our power systems and install a large number of charging stations, but conventional planning methods are not up to the task. By applying advanced simulation and optimization tools, we can design a smarter, more cost-effective electric transportation network. The initial focus was on public transit systems, demonstrating how this approach can deliver broader economic, reliability, and air quality benefits nationwide.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗

Essential Autonomous Science Inference on Rovers (EASIR)

Existing constraints on time, computational, and communication resources associated with Mars rover missions suggest on-board science evaluation of sensor data can contribute to decreasing human-directed operational planning, optimizing returned science data volumes, and recognition of unique or novel data. All of which act to increase the scientific return from a mission. Many different levels of science autonomy exist and each impacts the data collected and returned by, and activities of, rovers. Several computational algorithms, designed to recognize objects of interest to geologists and biologists, are discussed. The algorithms represent various functions that producing scientific opinions and several scenarios illustrate how the opinions can be used.

Roush, Ted L.↗

Goal Selection for Embedded Systems with Oversubscribed Resources

We describe an efficient, online goal selection algorithm and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗

Onboard Run-Time Goal Selection for Autonomous Operations

We describe an efficient, online goal selection algorithm for use onboard spacecraft and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗

Tractable Goal Selection with Oversubscribed Resources

We describe an efficient, online goal selection algorithm and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗

Are better combinations of DERs more profitable?: Combinatorial optimization for aggregation of DERs in wholesale electricity markets

Recently, regulatory changes in various countries have enabled the participation of small-scale distributed energy resources (DERs) aggregated in virtual power plants (VPPs) in wholesale electricity markets. The inherent uncertainty and variability of resources comprising VPPs can lead to imbalances between forecasted and metered outputs, potentially resulting in the deficient settlement of generation under imbalance settlement rules. To address this challenge, it is essential to manage variability in the planning phase and uncertainty in the operation phase. Most current research focuses on managing forecasting errors in the operational phase, with insufficient attention given to the planning phase. Here, to bridge this gap, this paper proposes an optimal combination strategy for DERs to maximize the market participation revenue of VPPs by proactively managing variability in the planning phase. To estimate the expected revenue, we conducted analyses for homogeneous and heterogeneous DERs using Monte Carlo simulations and genetic algorithms. Remarkably, the proposed method demonstrated approximately 8 % higher revenue compared to the neighboring group case when considering diversity in DER set configuration with equal proportions of photovoltaics and wind.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Turning Limitations into Opportunities in the Development of the Orion Medical System: Incorporation of mHealth Devices

INTRODUCTION: Selection of medical devices for the Orion medical system is a complex task which is dependent on the current state of terrestrial technology. In this work we review the interplay between NASA requirements, constraints, and opportunities for synergy during the development of the Orion medical system. METHODS: The “plan to treat” list of conditions, and subsequently the medical resource list for the Orion Artemis II lunar flyby mission was completed using semi-quantitative methods. During this process, some medical resources were excluded to comply with mass and volume limits, while other resources applicable to multiple medical requirements were prioritized for inclusion. Choices were also examined considering NASA level of care standards for the Artemis design reference missions. As a means to optimize capabilities in spite of mass and volume constraints, ideas for integration of multiple devices into a single platform were explored, including a ‘hackathon’ challenge which was conducted to generate and evaluate concepts for combining medical devices into a single app-based mobile device (ultrasound, ECG, etc.). RESULTS: The Orion team identified 128 medical conditions that we “plan to treat”, with 139 unique medical resources to address these conditions, including 5 digital diagnostic devices (ECG, otoscope, stethoscope, pulse oximeter, and blood pressure monitor). During selection of these digital devices the team noted that miniaturized medical devices often use mobile device platforms (mHealth), some displaying and transmitting data exclusively via mobile device. Of the 5 initially selected devices, all are capable of mobile connection, one which cannot function without a mobile device (ECG). Furthermore, only one of these devices connects natively to a Windows platform, which is currently the only operating system available on Orion. DISCUSSION: Significant savings in mass and volume as well as training and usability improvements can be achieved by leveraging mHealth technologies. However, the platform presents significant challenges for deployment within the Artemis Program including lack of internet connectivity, incompatible operating systems, and radiation concerns. Each of these drawbacks are surmountable with investment in the supporting vehicle architecture, which may become necessary to support the technology trends seen in commercially available medical devices today. Objective: Learn about the opportunities and challenges of leveraging mHealth devices in the development of medical capabilities for austere environments. Learn about the constraints of the NASA spaceflight environment with regards to digital medical device integration.

Douglas Ebert↗

What Can We Learn from US National Transmission Studies?

Multiple US regions have announced new electricity transmission plans, are actively revisiting the future role of transmission, and could benefit from findings from recent national-scale transmission studies. A review of seven national studies shows that significant transmission expansion is cost-optimal for serving new demand, integrating additional resources, and supporting grid reliability. A majority of the reviewed scenarios, which span a range of policy and technology assumptions, include at least a doubling of the transmission system by 2050. The national studies find substantial net system cost savings from transmission expansion and high benefit-cost ratios for transmission investments. The results are derived through multi-value, nationally coordinated, co-optimized, multi-scenario modeling, which is an approach that could yield lower-cost pathways compared to current industry planning practices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dispatch Optimization Variable Engine

The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.

McDowell, DylanJ. [Idaho National Laboratory (INL)↗

Mars scouts: an overview

The Mars program institutes the Mars Scout Missions in order to address science goals in the program not otherwise covered in the baseline Mars plan. Mars Scout Missions will be Principle-Investigator (PI) led science missions. Analogous to the Discovery Program, PI led investigations optimize the use of limited resources to accomplish the best focused science and allow the flexibility to quickly respond to discoveries at Mars. Scout missions also require unique investments in technology and reliance upon Mars-based infrastructure such as telecom relay orbiters.

mars scout missions↗

Revolutionary Deep Space Science Missions Enabled by Onboard Autonomy

Breakthrough autonomy technologies enable a new range of spire missions that acquire vast amounts of data and return only the most scientifically important data to Earth. These missions would monitor science phenomena in great detail (either with frequent observations or at extremely high spatial resolution) and onboard analyze the data to detect specific science events of interest. These missions would monitor volcanic eruptions, formation and movement of aeolian features. and atmospheric phenomena. The autonomous spacecraft would respond to science events by planning its future operations to revisit or perform complementary observations. In this paradigm, the spacecraft represents the scientists agent enabling optimization of the downlink data volume resource. This paper describes preliminary efforts to define and design such missions.

autonomy↗

Developing Mars-Based Clinical Scenarios for an Earth Independent Medical Operations (EIMO) – Based Decision Support Service

As crewed missions move beyond Low-Earth Orbit, pre-mission planning cannot fully buy down the medical risks of exploration-class missions. Martian missions, where increased hazards exist, (such as long-duration spaceflight, surface-level EVA operations, and communications delays) will require a paradigm shift in the structure of a medical system. An Earth-Independent Medical Operations-based Medical System (EIMO-MS) will need to optimize four critical domains to help provide medical care: utilization of Pre-Mission Planning, augmentation of Acute and Prolonged Medical Decision Making, automated tracking of Resource Management, and assistance in Task Load Balance. The ideal EIMO-MS will be able to accomplish this goal by having an interactive, adaptable interface that will be able to provide real-time medical services. It must respond based on the level of crewmember training, medical situation, and available medical and non-medical resources. To showcase the capabilities and requirements of such a sophisticated automated MS, a series of clinical scenarios of escalating complexity were developed with clinical and systems engineering input. These scenarios describe in clinical detail what a theoretical future medical system, enhanced with multiple information streams (such as a medical database, an AI-based Decision Support System, real-time monitoring, enhanced in-situ laboratory imaging, etc.) can achieve in conjunction with a trained and experienced crew. Scenarios are comprised of: a context section including objectives and applicable spaceflight environment, a highlighted assumptions section, a clinical narrative section, and a systems engineering activity diagram demonstrating the integrated Medical System (MS). The “swim lanes” of the activity diagram act as the logistical core of each scenario and show how the MS will interact with the crew, ground support, and other in-flight systems. The Design Reference Mission that is used for the scenarios is based on existing reference mission profiles [1] with a projected 30-sol stay on the Martian surface. Scenarios span the spectrum from planned evaluations, minor medical care, urgent care, surgical guidance, critical and expectant management, and behavioral health care. Mission complexity will exponentially increase during deep space and Mars exploration-class missions, and medical support for these missions will likewise need to increase in autonomy and adaptability. The integrated system that will support these missions will need to provide assistance in a variety of anticipated and unforeseen scenarios. These medical scenarios, guided by clinician input, are initial steps in crafting the requirements for an EIMO-based medical system. By working in a systems engineering framework, requirements and capabilities can be extracted and mapped while maintaining a clinical core.

Prashant Parmar↗

IV&V Planning & Execution Initiative

Independent verification and validation (IV&V) is a systems engineering discipline which seeks to provide confidence that mission-critical software-dependent systems will operate safely and achieve all mission objectives. In order to optimize application of IV&V resources, it is necessary to identify specific assurance objectives that are most likely to reveal difficulty and therefore to increase confidence. Software assurance literature deals predominantly with the code itself. However, our experience is that the most significant software-related issues are discovered via analysis of other system artifacts such as operations concepts, requirements and design. Consequently, it is desirable to, when assessing risk and defining assurance objectives, consider all facets of the software system architecture. We describe in this presentation progress and lessons learned from an IV&V capability development initiative to enhance the IV&V project planning process using all available architecture information.

Risk↗

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Health and Pharmacogenomics

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expand in duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to tailor medications for individual crewmembers and further examine appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique clinical and environmental history, genetic makeup, and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. A subset of this field is pharmacogenomics (PGX), the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on drug choice and dosing to avoid adverse events and maximize efficacy. The study goal was to identify which current space pharmacy drugs could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs on the ISS was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both astronauts’ personal medications, including supplements and over the counter drugs (n=151) contained in the ISS medical accessory kit (IMAK), and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in a total of 157 drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure (LxC). Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent ineffective treatment or impactful side effect events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost, or technical criteria and ranked from 1 (very low) to 5 (very high). An assessment of PGX reference laboratories is currently underway to evaluate sample requirements, benefit analysis (cost vs. utility of allele variant analysis), relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments (LxC 5x5 table) indicated 128 medications were in the green zone where risk is acceptable, with the remaining 29 of the medications in the yellow or red zone driven predominantly due to drug failure or safety concerns. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive preflight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve drug efficacy, and further open the door to countermeasure research. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more effective and efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing selection of the best treatment choice, and providing tailored countermeasures for individual crewmembers.

Pharmacogenomics↗

Mars Scout 2007 - a current status

The Mars Program institutes the Mars Scout Missions in order to address science goals in the program not otherwise covered in baseline Mars plans. Mars Scout missions will be Principal-Investigator (PI) led science missions. Analogous to the Discovery Program, PI-led investigations optimize the use of limited resources to accomplish focused science and allow the flexibility to quickly respond to discoveries at Mars. Scout missions also require unique investments in technology and reliance upon Mars-based infrastructure such as telecom relay orbiters. Scouts utilize a two-step competitive process for selection. In Dec, 2002, the Step 2 selections by NASA were announced and then approximately five month studies will result in a selection for flight around August, 2003 for a mission to be launched in 2007.

Mars Scout↗

Adaptive Sensing of Time Series with Application to Remote Exploration

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

artificial intelligence↗