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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 1,063 records · Page 59

Optical Instrument Thermal Control on the Large Ultraviolet/Optical/Infrared Surveyor

The Large Ultraviolet/Optical/Infrared Surveyor (LUVOIR) is a multi-wavelength observatory commissioned by NASA as one of four large mission concept studies for the Astro2020 Decadal Survey. Two concepts are under study which bound a range of cost, risk, and scientific return: an 8-meter diameter unobscured segmented aperture primary mirror and a 15-meter segmented aperture primary mirror. Each concept carries with it an accompanying suite of instruments. The Extreme Coronagraph for Living Planetary Systems (ECLIPS) is a near-ultraviolet (NUV) / optical / near-infrared (NIR) coronagraph; the LUVOIR Ultraviolet Multi-object Spectrograph (LUMOS) provides multi-object imaging spectroscopy in the 100-400 nanometer ultraviolet (UV) range; and the High Definition Imager (HDI) is a wide field-of-view near-UV / optical / near-IR camera that can also perform astrometry. The 15-meter concept also contains an additional instrument, Pollux, which is a high-resolution UV spectro-polarimeter. While the observatory is nominally at a 270 Kelvin operational temperature, the requirements of imaging in both IR and UV require separate detectors operating at different temperature regimes, each with stringent thermal stability requirements. The change in observatory size requires two distinct thermal designs per instrument. In this current work, the thermal architecture is presented for each instrument suite. We describe here the efforts made to achieve the target operational temperatures and stabilities with passive thermal control methods. Additional discussion will focus on how these instrument thermal designs impact the overall system-level architecture of the observatory and indicate the thermal challenges for hardware implementation.

LUVOIR↗

Thermal Development of a Commercial off the Shelf (COTS) Camera for Exploration Upper Stage (EUS)

NASA’s Flight Imagery Launch Monitoring Real-time System (FILMRS) cameras were originally developed for the Space Launch System (SLS) Core Stage. These Commercial Off the Shelf (COTS) cameras have been redesigned and reduced by an order of magnitude in size for the Exploration Upper Stage (EUS). The change in thermal environment has led to the application of various passive thermal control methods and the addition of a heater option. This paper will give a summary of the design and development test effort associated with adapting the COTS camera for the demands of the space environment and associated thermal mitigations applied as the project prepares to complete the design. The application of this camera for other space systems is discussed.

Hernandez, Deborah↗

Integrated system for sensing and traverse of cliff faces

In this paper, we describe the development of an integrated suite of autonomous, adaptive hardware/software control methods called SMART (System for Mobility and Access to Rough Terrain) that enables mobile robots to explore potentially important science sites currently beyond the reach of conventional rover designs.

cooperative↗

Dawn's operations in cruise from Vesta to Ceres

On 5 September 2012, Dawn concluded its successful exploration of Vesta, the second most massive object in the main asteroid belt. The spacecraft departed after 14 months in orbit and is now using its ion propulsion system to travel to dwarf planet Ceres, the most massive main-belt asteroid. The principal activity now is thrusting with the ion propulsion system to provide the 3.3 km/s required to rendezvous with Ceres early in 2015. Because two of the four reaction wheels have experienced faults and are likely unrecoverable, a substantial effort has been invested in preparing for Ceres operations with alternate attitude control methods. The project has engaged in an intensive campaign to reduce hydrazine expenditures, which has resulted in a significant increase in the hydrazine expected to be available for Ceres. Based on this work, studies provide good confidence that the required activities at Ceres can be completed. This paper describes post-Vesta operations, including measures taken to conserve hydrazine as well as other preparations for Ceres.

Mase, Robert A.↗

Event Report for The Ethical Artificial Intelligence Quantification Workshop

Artificial Intelligence (AI) is a powerful emerging technology area which requires special attention to using it ethically. AI ethics is still an emerging field, and the partners for this workshop and report seek to move AI ethics discussion ahead by experimenting with ways to measure AI ethics criteria. The following document describes the outcomes and learnings from The Ethical Artificial Intelligence Quantification Workshop held at the National Institute for Aerospace (NIA), Hampton, Virginia on May 12th, 2022. The purpose of the workshop was for participants to evaluate and experiment-with the methodology and process presented by AIEthics.World in cooperation with Intel Corporation. The meeting participants learned about the Ethical AI Certification and Maturity Model™ and applied the methodology to selected notional AI systems. The workshop facilitated the evaluation of the maturity of the AI system according to ethical considerations relevant to NASA, NIA and other participants. The workshop consisted of three main phases. The first phase focused on understanding and summarizing NASA’s ethical approaches, mission and values based on published documentation, discussions and individual insights & opinions of participants. This information was prioritized, weighted, ordered, and quantified in phase two, to formulate an alignment between human values (ethics) and their applicability to AI systems during all lifecycle phases. The first two phases were summarized as a form of ethical genealogy for artificial intelligence, specific to NASA’s ethical approaches. In the third and last phase of the workshop the participants evaluated notional examples of artificial intelligence to qualify and quantify its ability to adhere to the organizational ethics approaches, using the Ethical AI Certification and Maturity Model™. The workshop uses the concept of genealogy, in the traditional sense: the study and traceability of lines of ancestors in the process of evolutionary development from earlier forms. However, as it is applied to an Ethical AI definition, it is providing the insights to the necessary and mandatory traceability of content, data, metrics, telemetry, elements, and structures which are used in the AI’s lifecycle to foster and measure AI ethics in all steps of its lifecycle. The Ethical Artificial Intelligence Quantification Workshop provided NASA with the opportunity to apply the Ethical AI Certification and Maturity Model™, in combination with existing and well-known decision-making and quality control methods to identify the metrics and measurements for an Ethical AI and assess its ethical condition and quality aligned with NASA ethics approaches. The result of the workshop is the capacity for NASA to apply the maturity model assessment to its AI Systems as desired and if necessary, publish the ability of these AI Systems to adhere to the organizational ethical goals. AI ethics frameworks need to be customized for each application domain, for example, individual NASA Mission Directorates. General principles that work in one area such as AI/Machine Learning-based text analysis (the ethics of information-extraction) may need to be adapted for another such as sense-and-avoid decision-making in a flight environment. The workshop was conducted among approximately twenty NASA subject matter experts, so the elements noted above should be considered examples, not definitive NASA ethical AI principles, genealogy, etc. Generating a definitive AI ethics framework for an organization as diverse as NASA would require far more discussion, debate, review, etc. However, the workshop provided valuable insight into mechanisms and processes for quantifying AI ethical qualities.

Artificial Intelligence↗

Effect of Strict Head Down Tilt Bedrest on Pituitary Gland Height

BACKGROUND Pituitary gland deformity and loss of pituitary height have been identified in astronauts postflight, hypothesized to be related to increased intracranial pressure or intracranial pressure pulsatility exposure from prolonged weightlessness. Microgravity-induced chronic headward fluid shift has been suggested as a root cause of intracranial compliance changes leading to altered intracranial pressure dynamics. Elevated intracranial pressure or pressure pulsatility is theorized to promote the development of an arachnoid diverticulum, which herniates into the pituitary fossa via a defect in the diaphragma sellae compressing the pituitary gland. We aimed to determine if chronic headward fluid induced by strict head-down tilt bed rest (HDTBR) can cause similar quantitative changes in pituitary gland height. METHODS Control group data from two 6-degree HDTBR studies were analyzed (SANS CM and AGBRESA). The AGBRESA study collected MRI data at Baseline, 14 days into HDTBR (HDTBR-14), 52 days into HDTBR (HDTBR-52), and three days into Recovery (R+ 3) and included eight healthy adults (2 women), age = 33 ± 8 years. The SANS CM collected MRI data at Baseline, 15 days into HDTBR (HDTBR-15), 29 days into HDTBR (HDTBR-29), and 12 days into Recovery (R+12) and included twelve healthy adults (4 women), age = 34 ± 9 years. Pituitary gland height was evaluated using a sagittal, 3D T1-MPRAGE sequence obtained on a dedicated 3T Siemens Biograph MRI scanner using a 32-channel head coil. Following the reconstruction of a true orthogonal sagittal plane of the pituitary gland using a 3D multiplanar reconstruction tool (Horosproject.org), the anterior pituitary mid-gland height at the pituitary stalk level was quantified according to the methodology described by Kramer et al. . A paired t-test was used to evaluate changes from the baseline measurements. FINDINGS The mean height of the pituitary gland at baseline was 6.5 ± 1.7 mm (AGBRESA) and 5.7 ± 1.6 mm (SANS CM). From baseline measurements, the SANS CM STUDY data showed a decrease in mean pituitary height of 0.3 mm (p=.011) at HDTBR-15, 0.5 mm at HDTBR-29 (p<.001) and 0.2 mm at R+12 (p=.02). From baseline measurements, the AGBRESA data showed a decrease in mean pituitary height of 0.3 mm (p=.06) at HDTBR-14, 0.6 mm at HDTBR-52 (p<.002) and 0.2 mm at R+3 (p=.13). CONCLUSION HDTBR results in progressive loss of pituitary height, which is most severe with the longest HDTBR exposure. Early pituitary height loss was the same at HDTBR-14 (AGBRESA) and HDTBR-15 (SANS CM). Residual pituitary height loss was the same at R+12 and R+3 but only significant in the latter (SANS CM). The degree of pituitary height loss at HDTBR-52 replicates the 0.6 mm height loss found in long-duration astronauts after approximately six months of microgravity exposure (p<.01, preflight mean height=5.9 mm). The hormonal effects of pituitary height loss are unknown in astronauts and HDTBR subjects and should be investigated in future studies. Future work will examine the individual variability in the loss of pituitary gland height and whether those changes are associated with other SANS findings, such as optic disc edema.

L A Kramer↗

Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking: Preprint

As distributed energy resources play an increasing role in generation and grid services, control and market paradigms will need to be tested with models that incorporate transmission and distribution systems. The test systems will need to be realistic and accessible for researchers to form conclusions about realistic behaviors and maintain comparability and repeatability of results. These test systems also must have high resolution models of sufficient size for realistic distribution and transmission interaction. This paper demonstrates the tightly coupled co-simulation of realistic synthetic distribution and transmission models for the Austin metropolitan area and how this framework can be used to analyze resultant behaviors from distributed resources and their controls. The comparison of a distribution system run with fixed feed-in voltage is compared to the closely tied distribution-transmission co-simulation. It is determined that even without advanced voltage controls, the feed-in voltage response of the transmission system shows a lower level of voltage excursions. Therefore, control methods for voltage stability should be benchmarked on realistic transmission and distribution co-simulations for more accurate assessment of voltage profiles.

27 ARPA - Advanced Research Projects Agency-Energy↗

Systems and methods for cylinder deactivation in dedicated EGR engine

Systems, apparatus, and methods are disclosed that include a divided exhaust engine with at least one primary exhaust gas recirculation (EGR) cylinder and a plurality of non-primary EGR cylinders. The systems, apparatus and methods control the EGR fraction by deactivation of one or more of the cylinders.

Desai, Akash S.↗

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework: Preprint

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb and observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. The proposed DERMS online platform is generalizable to deal with various types of distributed energy resources (DERs), including distributed photovoltaics (PVs), energy storage, electric vehicles, demand response, etc. Comparison results with other control methods on a realistic distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resources management↗

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗

NMPC for Setpoint Tracking Operation of a Solid Oxide Electrolysis Cell System

Solid oxide electrolysis cells (SOECs) are a promising technology to generate hydrogen through water electrolysis. However, intermittent renewable energy requires SOECs to transition between hydrogen production setpoints as the price of electricity fluctuates. A well-functioning control system is important to avoid cell degradation during setpoint tracking operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOEC module and supporting equipment and compare NMPC performance to classical PI control while ramping between hydrogen production setpoints. We find that these control methods provide similar performance in many metrics, but NMPC significantly reduces cell thermal gradients during the setpoint transition.

Allan, Douglas↗

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management: Preprint

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak load demand shaving. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operation to enhance the control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment for peak demand reduction.

deep reinforcement learning↗

Electrochemical polymer pen lithography

Disclosed herein is a massively parallel patterning tool for the deposition of single metals or metal alloys with size and composition control. Methods of the disclosure use a hydrogel array of pyramidal pen tips as a medium for localized electrodeposition, in conjunction with a scanning probe lithography platform and a three-electrode cell. This versatile technique can be used for high-throughput 3D printing, biomolecule patterning, or screening of catalyst nanoparticles or thin films.

Mirkin, Chad A.↗

Assessment of Cold Spraying Mild-Steel Powder onto Mild-Steel Substrate for Development of Waste Tank Repair System - 20515

Infrastructure for nuclear waste storage and processing (e.g., waste tanks, transfer pipelines, evaporators) at the U.S. Department of Energy (DOE) Hanford Site has been in service well beyond its original design life. Past corrosion control methods at Hanford for waste tanks have not been fully successful, as evidenced by leaks forming in tank AY-102, the first double-shell tank (DST) constructed, and significant degradation detected in the primary tanks of AP-102 and AY-101. Failure of infrastructure components can pose a significant risk to the environment, worker safety, and project schedules. Therefore, remotely deployable methods for repairing and extending the service life of the existing tank waste infrastructure are needed. Cold spray has been identified as a potential technique for performing in situ repairs and material buildup for life extension of waste storage and processing infrastructure. Cold-spray repair methods and technology are well-established and are used extensively by industry and the military for making repairs using dissimilar materials. Pacific Northwest National Laboratory is evaluating the process of making repairs using mild-steel powder applied to a mild-steel substrate to minimize the galvanic corrosion potential. This paper presents the initial results for a feasibility ('go/no-go') assessment as to whether low-density deposits with sound metallurgic bonds, to build-back steel plate material, can be achieved using existing commercial cold-spray equipment. An assessment of steel-on-steel deposit is necessary to determine if cold spray is a viable candidate for DST carbon steel plate restoration/repair and thus DST service life extension. Powder properties and preparation requirements have been investigated and operating conditions and parameters for depositing a cold-spray buildup of mild steel on a mild-steel substrate have been determined. Soundness of metallurgic bonding as a function of the operating parameters exercised and results from applying cold spray to lay a deposit over simulated small-diameter flaws in 1/2-inch mild-steel plate are presented. Application of in situ cold-spray repair to the DOE complex has the potential to reduce cost and schedule impacts associated with component failures and the need to procure and construct replacement infrastructure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Examining the Feasibility of Identifying Tau Neutrino Charged Current Events in the DUNE Far Detector

Neutrinos began as theoretical, massless particles, and since their first detection they have continued to be the subject of various experiments. One such experiment is DUNE, which is a long baseline neutrino experiment with the goal of studying neutrino properties, such as neutrino oscillation parameters. In this work, two projects were completed, one dealing with the hardware of DUNE and the other dealing with neutrino simulations. For the hardware project, we designed a quality control method for testing adaptor boards which make up part of the Far Detector circuit boards. This method was completed and prototyped, however was not implemented as planned due to funding changes. For the simulation project, we simulated ντ , νµ, and νe CC interactions using two simulation methods (stand alone GENIE and a full detector simulation) in order to begin to understand what a ντ CC event would look like in the Far Detector and create an initial list of kinematic properties that can be used for this purpose. We found that there is not a complete understanding of what is occurring in the full detector simulation. We also found that there is promise in using kinematic properties to be able to differentiate ντ CC events, however properties beyond those covered here, as well as a more accurate simulation, will be required for any definitive statistical statements.

Choate, Sarah↗

Reinforcement Learning to Enhance Optimal Operation of Resilient Community Energy Systems

This paper presents a novel model-free multi-agent Reinforcement Learning (RL) control method to enhance the resilience of community energy systems in island mode, which coordinates multiple objectives without the necessity of identifying system models that require expert knowledge. Specifically, a community-level coordinator agent is designed to allocate renewable energy resources among different buildings, and multiple building-level agents are developed to optimize load schedules based on limited energy resources and requirements of building loads and occupants’ comfort. In a two-day evaluation, our RL approach demonstrated a similar performance against MPC without requiring system models and formulation of optimization problems as required in MPC.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Dynamic Simulation Modeling and Control of a Desiccant Assisted Direct-expansion Air Handling Unit

Desirable built environments demand simultaneous regulation of thermal comfort and indoor air quality (IAQ) with energy-efficient operation of heating, ventilation and air conditioning (HV AC) systems, which involves controls of temperature, humidity and airborne contaminants simultaneously. This paper presents the efforts of dynamic modeling and initial development control strategy for a desiccant-assisted multi-functional air handling unit (AHU) coupled with a direct-expansion rooftop unit (RTU) system, which aims to achieve multiple functions for indoor environment conditioning with energy efficient control. The RTU-AHU system includes a desiccant wheel for dehumidification and a conceptual direct air capture (DAC) filtering device for CO2 regulation. A Modelica-based dynamic model is developed for this conceptual system, and a simple decentralized control strategy is designed, which combines a differential-enthalpy based AHU return-air ratio control, a demand-controlled ventilation, and supply-air temperature humidity control via the RTU and DW controls. The proposed control method is evaluated with the Modelica simulation model for a selected set of scenarios

Pan, Chao↗