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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

Building control↗
DOE OSTI2021

Hardware-In-the-Loop Benchmarking Setup for Phasor Based Control Validation

Phasor Based Control is a novel approach to controlling Distributed Energy Resources that aims at relieving various constraints that arise in the distribution grid. It is a two-layer control system with a supervisory control that coordinates distributed controllers to reach voltage phasor targets. The distributed controllers use local synchrophasor measurements and operate as feedback controllers. This control method is currently under development with several algorithms being under consideration for both the central and distributed components. In this report, we present the experimental setup that was prepared to prototype a hardware implementation and validate the control method in Hardware-In-the-Loop.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Hardware-In-the-Loop Benchmarking Setup for Phasor Based Control Validation

Phasor Based Control is a novel approach to controlling Distributed Energy Resources that aims at relieving various constraints that arise in the distribution grid. It is a two-layer control system with a supervisory control that coordinates distributed controllers to reach voltage phasor targets. The distributed controllers use local synchrophasor measurements and operate as feedback controllers. This control method is currently under development with several algorithms being under consideration for both the central and ditributed components. In this paper, we present the experimental setup that was prepared to prototype a hardware implementation and validate the control method in Hardware-In-the-Loop.

Baudette, Maxime↗
NASA NTRS2012

Next-Generation Evaporative Cooling Systems for the Advanced Extravehicular Mobility Unit Portable Life Support System

The development of the Advanced Extravehicular Mobility Unit (AEMU) Portable Life Support System (PLSS) is currently underway at NASA Johnson Space Center. The AEMU PLSS features two new evaporative cooling systems, the Reduced Volume Prototype Spacesuit Water Membrane Evaporator (RVP SWME), and the Auxiliary Cooling Loop (ACL). The RVP SWME is the third generation of hollow fiber SWME hardware, and like its predecessors, RVP SWME provides nominal crewmember and electronics cooling by flowing water through porous hollow fibers. Water vapor escapes through the hollow fiber pores, thereby cooling the liquid water that remains inside of the fibers. This cooled water is then recirculated to remove heat from the crewmember and PLSS electronics. Major design improvements, including a 36% reduction in volume, reduced weight, and more flight like back-pressure valve, facilitate the packaging of RVP SWME in the AEMU PLSS envelope. In addition to the RVP SWME, the Auxiliary Cooling Loop (ACL), was developed for contingency crewmember cooling. The ACL is a completely redundant, independent cooling system that consists of a small evaporative cooler--the Mini Membrane Evaporator (Mini-ME), independent pump, independent feed-water assembly and independent Liquid Cooling Garment (LCG). The Mini-ME utilizes the same hollow fiber technology featured in the RVP SWME, but is only 25% of the size of RVP SWME, providing only the necessary crewmember cooling in a contingency situation. The ACL provides a number of benefits when compared with the current EMU PLSS contingency cooling technology; contingency crewmember cooling can be provided for a longer period of time, more contingency situations can be accounted for, no reliance on a Secondary Oxygen Vessel (SOV) for contingency cooling--thereby allowing a SOV reduction in size and pressure, and the ACL can be recharged-allowing the AEMU PLSS to be reused, even after a contingency event. The development of these evaporative cooling systems will contribute to a more robust and comprehensive AEMU PLSS.

Makinen, Janice V.↗
NASA NTRS2015

Human Research Program Advanced Exercise Concepts (AEC) Overview

Exercise countermeasures provide benefits that are crucial for successful human spaceflight, to mitigate the spaceflight physiological deconditioning which occurs during exposure to microgravity. The NASA Human Research Program (HRP) within the Human Exploration and Operations Mission Directorate (HEOMD) is managing next generation Advanced Exercise Concepts (AEC) requirements development and candidate technology maturation to Technology Readiness Level (TRL) 7 (ground prototyping and flight demonstration) for all exploration mission profiles from Multi Purpose Crew Vehicle (MPCV) Exploration Missions (up to 21 day duration) to Mars Transit (up to 1000 day duration) missions. These validated and optimized exercise countermeasures systems will be provided to the ISS Program and MPCV Program for subsequent flight development and operations. The International Space Station (ISS) currently has three major pieces of operational exercise countermeasures hardware: the Advanced Resistive Exercise Device (ARED), the second-generation (T2) treadmill, and the cycle ergometer with vibration isolation system (CEVIS). This suite of exercise countermeasures hardware serves as a benchmark and is a vast improvement over previous generations of countermeasures hardware, providing both aerobic and resistive exercise for the crew. However, vehicle and resource constraints for future exploration missions beyond low Earth orbit will require that the exercise countermeasures hardware mass, volume, and power be minimized, while preserving the current ISS capabilities or even enhancing these exercise capabilities directed at mission specific physiological functional performance and medical standards requirements. Further, mission-specific considerations such as preservation of sensorimotor function, autonomous and adaptable operation, integration with medical data systems, rehabilitation, and in-flight monitoring and feedback are being developed for integration with the exercise countermeasures systems. Numerous technologies have been considered and evaluated against HRP-approved functional device requirements for these extreme mission profiles, and include wearable sensors, exoskeletons, flywheel, pneumatic, and closed-loop microprocessor controlled motor driven systems. Each technology has unique advantages and disadvantages. The Advanced Exercise Concepts project oversees development of candidate next generation exercise countermeasures hardware, performs trade studies of current and state of the art exercise technologies, manages and supports candidate systems physiological evaluations with human test subjects on the ground, in flight analogs and flight. The near term goal is evaluation of candidate systems in flight, culminating in an integrated candidate next generation exercise countermeasures suite on the ISS which coalesces research findings from HRP disciplines in the areas of exercise performance for muscle, bone, cardiovascular, sensorimotor, behavioral health, and nutrition for optimal benefit to the crew.

Countermeasures↗
DOE OSTI2020

Lab-Scale, Closed-Loop Experimental Characterization, Model Refinement, and Validation of a Hydrokinetic Energy-Harvesting Ocean Kite

This paper presents a study wherein we experimentally characterize the dynamics and control system of a lab-scale ocean kite, and then refine, validate, and extrapolate this model for use in a full-scale system. Ocean kite systems, which harvest tidal and ocean current resources through high-efficiency cross-current motion, enable energy extraction with an order of magnitude less material (and cost) than stationary systems with the same rated power output. However, an ocean kite represents a nascent technology that is characterized by relatively complex dynamics and requires sophisticated control algorithms. In order to characterize the dynamics and control of ocean kite systems rapidly, at a relatively low cost, the authors have developed a lab-scale, closed-loop prototyping environment for characterizing tethered systems, whereby 3D printed systems are tethered and flown in a water channel environment. While this system has been shown to be capable of yielding similar dynamic characteristics to some full-scale systems, there are also fundamental limitations to the geometric scales and flow speeds within the water channel environment, making many other real-world scenarios impossible to replicate from the standpoint of dynamic similarity. Here, to address these scenarios, we show how the lab-scale framework is used to refine and validate a scalable dynamic model of a tethered system, which can then be extrapolated to full-scale operation. In this work, we present an extensive case study of this model refinement, validation, and extrapolation on an ocean kite system intended for operation in the Gulf Stream or similar current environments.

42 ENGINEERING↗
NASA NTRS2012

Magnetic Field Effects on Plasma Plumes

Here, we will discuss our numerical studies of plasma jets and loops, of basic interest for plasma propulsion and plasma astrophysics. Space plasma propulsion systems require strong guiding magnetic fields known as magnetic nozzles to control plasma flow and produce thrust. Propulsion methods currently being developed that require magnetic nozzles include the VAriable Specific Impulse Magnetoplasma Rocket (VASIMR) [1] and magnetoplasmadynamic thrusters. Magnetic nozzles are functionally similar to de Laval nozzles, but are inherently more complex due to electromagnetic field interactions. The two crucial physical phenomenon are thrust production and plasma detachment. Thrust production encompasses the energy conversion within the nozzle and momentum transfer to a spacecraft. Plasma detachment through magnetic reconnection addresses the problem of the fluid separating efficiently from the magnetic field lines to produce maximum thrust. Plasma jets similar to those of VASIMR will be studied with particular interest in dual jet configurations, which begin as a plasma loops between two nozzles. This research strives to fulfill a need for computational study of these systems and should culminate with a greater understanding of the crucial physics of magnetic nozzles with dual jet plasma thrusters, as well as astrophysics problems such as magnetic reconnection and dynamics of coronal loops.[2] To study this problem a novel, hybrid kinetic theory and single fluid magnetohydrodynamic (MHD) solver known as the Magneto-Gas Kinetic Method is used.[3] The solver is comprised of a "hydrodynamic" portion based on the Gas Kinetic Method and a "magnetic" portion that accounts for the electromagnetic behaviour of the fluid through source terms based on the resistive MHD equations. This method is being further developed to include additional physics such as the Hall effect. Here, we will discuss the current level of code development, as well as numerical simulation results

Ebersohn, F.↗
DOE OSTI2018

Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization

In many situations across computational science and engineering, multiple computational models are available that describe a system of interest. These different models have varying evaluation costs and varying fidelities. Typically, a computationally expensive high-fidelity model describes the system with the accuracy required by the current application at hand, while lower-fidelity models are less accurate but computationally cheaper than the high-fidelity model. Outer-loop applications, such as optimization, inference, and uncertainty quantification, require multiple model evaluations at many different inputs, which often leads to computational demands that exceed available resources if only the high-fidelity model is used. This work surveys multifidelity methods that accelerate the solution of outer-loop applications by combining high-fidelity and low-fidelity model evaluations, where the low-fidelity evaluations arise from an explicit low-fidelity model (e.g., a simplified physics approximation, a reduced model, a data-fit surrogate) that approximates the same output quantity as the high-fidelity model. The overall premise of these multifidelity methods is that low-fidelity models are leveraged for speedup while the high-fidelity model is kept in the loop to establish accuracy and/or convergence guarantees. We categorize multifidelity methods according to three classes of strategies: adaptation, fusion, and filtering. The paper reviews multifidelity methods in the outer-loop contexts of uncertainty propagation, inference, and optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1972

Fuel cell powerplant operation in Apollo spacecraft.

Primary electrical power for loads in the Apollo Command and Service Modules is furnished by a system of three fuel cell powerplants. The powerplants convert cryogenic hydrogen and oxygen into direct current. Water formed in the fuel cell reactions is supplied to the spacecraft for crew use. Waste heat is rejected through a coolant loop to a spacecraft radiator. The ability of the fuel cell to meet its voltage-power requirements and to control its own operating temperature under the environmental extremes of launch, ascent, earth orbit, translunar flight, and lunar orbit was demonstrated on successively more difficult missions leading up to the first lunar landing.

Ching, A. C.↗
NASA NTRS1985

Optical Quantum Receiver For Binary Signals

In quantum optical receiver, both amplitude and phase of received optical signal measured to extract as much information as possible, thereby reducing error probability. Phase-modulated received signal mixed with equal amplitude replica of optical carrier generated in phase locked loop. Two signals interfere with each other at photomultiplier cathode. Probability of error with this scheme close to theoretical minimum and implemented with current technology.

Vilnrotter, V. A.↗
NASA NTRS1985

An optimized rotation-axis model-following controller for STS orbiter attitude maneuvers

This paper describes a new controller for automatic attitude maneuvers of the Space Shuttle Orbiter. The controller incorporates a new solution algorithm for partially linearized, fuel-optimal maneuvers for RCS jet controlled spacecraft. These solutions provide model trajectories and jet commands that are easily tracked using a feed-forward, feedback controller structure. The result is a substantial performance improvement over the current Orbiter attitude maneuver controller. The paper discusses optimal maneuvers for this type of vehicle, giving detail of the solution algorithm. Closed-loop controller design and implementation is discussed. Detailed performance results are presented.

Redding, D. C.↗
NASA NTRS2000

Design and Operation of an Electrochemical Methanol Concentration Sensor for Direct Methanol Fuel Cell Systems

The development of a 150-Watt packaged power source based on liquid feed direct methanol fuel cells is being pursued currently at the Jet propulsion Laboratory for defense applications. In our studies we find that the concentration of methanol in the fuel circulation loop affects the electrical performance and efficiency the direct methanol fuel cell systems significantly. The practical operation of direct methanol fuel cell systems, therefore, requires accurate monitoring and control of methanol concentration. The present paper reports on the principle and demonstration of an in-house developed electrochemical sensor suitable for direct methanol fuel cell systems.

Narayanan, S. R.↗
NASA NTRS2009

Modeling and Simulation of Variable Mass, Flexible Structures

The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the distribution of mass in the fuel tank or Solid Rocket Booster (SRB) case for various propellant levels. Based on the mass consumed by the liquid engine or SRB, the appropriate propellant model is coupled with the dry structure model for the stage. Then using vehicle configuration data, the integrated vehicle model is assembled and operated on by the constant system shape functions. The system mode shapes and frequencies can then be computed from the resulting generalized mass and stiffness matrices for that mass configuration. The rigid body mass properties of the vehicle are derived from the integrated vehicle model. The coupling terms between the vehicle rigid body motion and elastic deformation are also updated from the constant system shape functions and the integrated vehicle model. This approach was first used to analyze variable mass spinning beams and then prototyped into a generic dynamics simulation engine. The resulting code was tested against Crew Launch Vehicle (CLV-)class problems worked in the TREETOPS simulation package and by Wilson [2]. The Ares I System Integration Laboratory (SIL) is currently being developed at the Marshall Space Flight Center (MSFC) to test vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment and certify that the integrated system is prepared for flight. The Ares I SIL utilizes the Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) tool to simulate the launch vehicle and stimulate avionics hardware. Due to the presence of vehicle control system filters and the thrust oscillation suppression system, which are tuned to the structural characteristics of the vehicle, ARTEMIS must incorporate accurate structural models of the Ares I launch vehicle. The ARTEMIS core dynamics simulation models the highly coupled nature of the vehicle flexible body dynamics, propellant slosh, and vehicle nozzle inertia effects combined with mass and flexible body properties that vary significant with time during the flight. All forces that act on the vehicle during flight must be simulated, including deflected engine thrust force, spatially distributed aerodynamic forces, gravity, and reaction control jet thrust forces. These forces are used to excite an integrated flexible vehicle, slosh, and nozzle dynamics model for the vehicle stack that simulates large rigid body translations and rotations along with small elastic deformations. Highly effective matrix math operations on a distributed, threaded high-performance simulation node allow ARTEMIS to retain up to 30 modes of flex for real-time simulation. Stage elements that separate from the stack during flight are propagated as independent rigid six degrees of freedom (6DOF) bodies. This paper will present the formulation of the resulting equations of motion, solutions to example problems, and describe the resulting dynamics simulation engine within ARTEMIS.

Tobbe, Patrick A.↗
NASA NTRS2011

Trajectory-Based Complexity (TBX): A Modified Aircraft Count to Predict Sector Complexity During Trajectory-Based Operations

In this paper we introduce a new complexity metric to predict -in real-time- sector complexity for trajectory-based operations (TBO). TBO will be implemented in the Next Generation Air Transportation System (NextGen). Trajectory-Based Complexity (TBX) is a modified aircraft count that can easily be computed and communicated in a TBO environment based upon predictions of aircraft and weather trajectories. TBX is scaled to aircraft count and represents an alternate and additional means to manage air traffic demand and capacity with more consideration of dynamic factors such as weather, aircraft equipage or predicted separation violations, as well as static factors such as sector size. We have developed and evaluated TBX in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center during human-in-the-loop studies of trajectory-based concepts since 2009. In this paper we will describe the TBX computation in detail and present the underlying algorithm. Next, we will describe the specific TBX used in an experiment at NASA's AOL. We will evaluate the performance of this metric using data collected during a controller-inthe- loop study on trajectory-based operations at different equipage levels. In this study controllers were prompted at regular intervals to rate their current workload on a numeric scale. When comparing this real-time workload rating to the TBX values predicted for these time periods we demonstrate that TBX is a better predictor of workload than aircraft count. Furthermore we demonstrate that TBX is well suited to be used for complexity management in TBO and can easily be adjusted to future operational concepts.

trajectories↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗
DOE OSTI2024

Modeling and Power-Hardware-in-the-Loop Validation of Synchronous Wind: An Inverterless Grid-Forming Wind Power Plant: Preprint

Grid-forming (GFM) control of Type-3 and Type-4 wind turbine generators has attracted substantial attention in power systems research; however, the limited over-current capability of power electronics converters continues to deteriorate the grid strength of the evolving power systems. Synchronous wind, also known as Type-5 wind turbine generator (WTG), offers a unique GFM solution to address grid integration and grid strength issues by keeping the grid largely synchronous at very high penetration levels of renewable generation. A Type-5 WTG interfaces to the electric grid via a synchronous generator (SG) driven by a variable-speed hydraulic torque converter; hence, the wind rotor operates in variable-speed mode for maximum power generation and the generator shaft remains synchronous to the grid. This paper developed and tested a high-fidelity model of Type-5 WTG under power-hardware-in-the-loop (PHIL) testing environment. The PHIL demonstration showed that a Type-5 WTGs inherently behaves as a GFM unit and can obtain similar performance in terms of power responses, wind rotor dynamics, and efficiency compared to Type-3 WTG in high wind conditions. The developed model also provides further insight on how Type-5 WTGs can benefit the smooth transition to power systems with high integration level of inverter-based resources.

grid strength↗
NASA NTRS1988

Understanding of and applications for robot vision guidance at KSC

The primary thrust of robotics at KSC is for the servicing of Space Shuttle remote umbilical docking functions. In order for this to occur, robots performing servicing operations must be capable of tracking a swaying Orbiter in Six Degrees of Freedom (6-DOF). Currently, in NASA KSC's Robotic Applications Development Laboratory (RADL), an ASEA IRB-90 industrial robot is being equipped with a real-time computer vision (hardware and software) system to allow it to track a simulated Orbiter interface (target) in 6-DOF. The real-time computer vision system effectively becomes the eyes for the lab robot, guiding it through a closed loop visual feedback system to move with the simulated Orbiter interface. This paper will address an understanding of this vision guidance system and how it will be applied to remote umbilical servicing at KSC. In addition, other current and future applications will be addressed.

Shawaga, Lawrence M.↗