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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Effects of Long-Duration Microgravity on Fine Motor Skills: ISS One-Year Mission

Fine motor skills will be critical in future long-duration missions, particularly those skills needed to interact with advanced technologies in next-generation vehicles, spacesuits, and habitats. Studies to date on the effects of microgravity and gravitational transitions on fine motor performance have not yielded conclusive results. Datasets are incomplete-timeline gaps in the microgravity data sessions. Studies have not focused on the fine motor actions that are likely to be required for interacting with software displays and controls (pointing, clicking, dragging, multi-touch/pinching). The majority of studies have used a joystick or arm reaching task. Touchscreen tablets are already in use on ISS, and at least one commercial partner is already planning a cockpit with touchscreens as the primary means of input. We must ensure that crewmembers are ready to perform with computer-based devices after a long-duration voyage and transition to surface operations.

Kritina Holden↗
NASA NTRS2017

Tack Measurements of Prepreg Tape at Variable Temperature and Humidity

NASA’s Advanced Composites Project has established the goal of achieving a 30 percent reduction in the timeline for certification of primary composite structures for application on commercial aircraft. Prepreg tack is one of several critical parameters affecting composite manufacturing by automated fiber placement (AFP). Tack plays a central role in the prevention of wrinkles and puckers that can occur during AFP, thus knowledge of tack variation arising from a myriad of manufacturing and environmental conditions is imperative for the prediction of defects during AFP. A full design of experiments was performed to experimentally characterize tack on 0.25-inch slit-tape tow IM7/8552-1 prepreg using probe tack testing. Several process parameters (contact force, contact time, retraction speed, and probe diameter) as well as environmental parameters (temperature and humidity) were varied such that the entire parameter space could be efficiently evaluated. Mid-point experimental conditions (i.e., parameters not at either extrema) were included to enable prediction of curvature in relationships and repeat measurements were performed to characterize experimental error. Collectively, these experiments enable determination of primary dependencies as well as multi-parameter relationships. Slit-tape tow samples were mounted to the bottom plate of a rheometer parallel plate fixture using a jig to prevent modification of the active area to be interrogated with the top plate, a polished stainless steel probe, during tack testing. The probe surface was slowly brought into contact with the pre-preg surface until a pre-determined normal force was achieved (2-30 newtons). After a specified dwell time (0.02-10 seconds), during which the probe substrate interaction was maintained under displacement control, the probe was retracted from the surface (0.1-50 millimeters per second). Initial results indicated a clear dependence of tack strength on several parameters, with a particularly strong dependence on temperature and humidity. Although an increase in either of these parameters reduces tack strength, a maximum in tack was predicted to occur under conditions of low temperature and moderate humidity.

Wohl, Christopher↗
NASA NTRS2019

Multidisciplinary Optimization of a Turboelectric Tiltwing Urban Air Mobility Aircraft

Urban air taxis, also known as urban air mobility (UAM) vehicles, are anticipated to be an area of significant market growth in the near future. These vehicles are typically vertical take-off and landing (VTOL) designs which are capable of carrying 1 to 30 passengers in an intra-urban environment with flights of less than 50 nautical miles. Development of UAM vehicles and their integration into the airspace will be enabled by advancements in a number of areas including electrified propulsion systems, structures, acoustics, automation, and controls. However, the strong multidisciplinary interactions for these unique vehicles presents a significant new design challenge. This work describes the development of a multidisciplinary analysis and optimization environment which can be used to support the conceptual design of these UAM vehicles, using efficient gradient based optimization with analytic derivatives. The tools included in this multidisciplinary analysis model the aircraft trajectory, vehicle aerodynamics, structures, and electrified propulsion system. The multidisciplinary environment created in this research is unique in that all the physics tools are tightly integrated together, with the trajectory model directly calling the aerodynamics, structures, and propulsion models. This multidisciplinary analysis environment is then demonstrated in the design optimization of a turboelectric tiltwing UAM vehicle concept.

Hendricks, Eric S.↗
NASA NTRS2019

Minimizing Sonic Boom Through Simulation-Based Design: The X-59 Airplane

One of NASA’s six Strategic Thrusts for aeronautics is “Innovation in Commercial Supersonic Aircraft,” with a vision of fast air travel widely available to the traveling public. Future supersonic aircraft will be efficient, affordable, and environmentally responsible, generating an acceptable level of en-route noise (sonic booms). The first major step is the ongoing construction of the new X-59 Quiet SuperSonic Technology X-plane to demonstrate technologies that reduce sonic booms to gentle thumps. By using highresolution Cart3D computational fluid dynamics simulations, the shape of the aircraft can be designed to control the non-linear interactions of shock waves to reduce the sonic boom noise on the ground to within outdoor ambient levels, thereby enabling supersonic overland flight.

Nemec, Marian↗
NASA NTRS2020

Sketch-to-Solution: A Case Study in RCS Aerodynamic Interaction

Thanks to recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a sketch-to-solution work flow is now possible for viscous computational fluid dynamic (CFD) simulations. With this workflow, a CFD application engineer provides geometry, boundary conditions, and flow parameters; and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation. To explore the benefits of this nascent capability, a conventional manual grid generation work flow is compared to this new automatic grid generation work flow for a given engineering question: What are the aerodynamic interactions caused by the reaction control system (RCS) on an entry vehicle? This case study indicates that while the automatic grid generation sketch-to- solution process is not yet mature, it is preferred over a manual grid generation work flow because it greatly reduces manual labor, eliminates many opportunities for human error, and provides grid sensitivity information.

Bill Kleb↗
NASA NTRS2019

SPARROW: A Steam Propelled Autonomous Retrieval Robot for Ocean Worlds

This paper presents the results of a NIAC Phase I study into the use of a propulsively hopping robot for the exploration of Europa’s rugged, icy surface. Named the“Steam Propelled Retrieval Robot for Ocean Worlds,” SPARROW is a multi-thruster robot passively gimballed within a protective, spherical shell, which enables it to freely rotate, self-right, and tumble over chaotic terrains. SPARROW is envisioned as a soccerball-sized payload to a primary lander mission. Europa’s abundant surface ice would be harvested as an in situ propellant source. The principal objective of SPARROW would be to increase the science return of a Europa landed asset by enabling access to distal, spatially distributed geologic units. The design of mobility systems for Europa is challenging, due in part to its almost entirely unconstrained surface topography and strength. Images returned by Voyager and Galileo yielded resolutions on the order of hundreds of meters per pixel, with localized regions reaching 6 meters per pixel—still far larger than a typical rover. A key benefit of SPARROW’s hopping, impact-tolerant design, is that it eliminates the need for a piori information on the terrain topography and surface strength; no surface reaction forces are required for motion. In this context, SPARROW is entirely terrain agnostic. In this paper we detail the results of three study objectives: i) to quantify the energy required to collect surface ice, change its phase, and maintain propellant temperature, ii) to identify control and estimation strategies that enable SPARROW to successfully reach, and return from, regions of scientific interest, and iii) to characterize the impact of SPARROW’s range on likely science return. Five water-based propellant architectures are presented alongside their mass, power, and volume requirements. Monte Carlo simulations of SPARROW hopping and tumbling over 1 km of glacial ice are summarized, characterizing SPARROW’s sensitivity to uncertainty in: initial conditions, thrust control, and cage-terrain interaction. Finally, a science traceability matrix is presented, which details the effect of sortie range on three science goals: constraining Europa’s evolutionary morphology, assessing sub-surface ocean habitability, and searching for life and/or biosignatures.

Phillips, Cynthia↗
NASA NTRSDate not supplied

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (i.e. urban and rural unmanned aircraft systems) ecosystem, NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV). HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with FMI to identify optimal approaches for displaying information for human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a controlled vehicle completed a takeoff, active flight, and landing sequence while automated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self-reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users would like greater configurability of the interface based on their personal information requirements, and they would like the opportunity to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could be introduced as a potential way to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

vertiplex↗
NASA NTRSDate not supplied

Corridor Design and Analysis for UAM Operations

The Urban Air Mobility (UAM) concept is a part of Advanced Air Mobility (AAM), a joint initiative between the Federal Aviation Administration (FAA), NASA, and industry to develop an air transportation system that uses new electric (i.e., green) air vehicles in geographical areas previously underserved by traditional aviation. Market forecast studies predict that there will be demand for alternate modes of air transportation using electric Vertical Take-off and Landing aircraft. UAM expands transportation networks by introducing short flights to move people and goods around metropolitan areas​. UAM is expected to improve mobility for the public, decongest road traffic, reduce trip time, and decrease strain on existing public transportation networks. Various challenges exist to make the introduction of UAM operations successful in the U.S. National Airspace System (NAS). These include but are not limited to integration with existing airports and airspace, provision of air traffic services (e.g., separation), vehicle design and certification, and community acceptance. The focus of this paper is on integration of UAM operations into the NAS via introduction of new airspace structures. UAM will operate within a regulatory, operational, and technical environment that is incorporated into the NAS​. As per the UAM Concept of Operations (ConOps), the FAA retains regulatory authority and is responsible for establishing operational parameters and maintaining oversight. The FAA’s UAM ConOps describes flights at low altitudes (below 5,000 ft) with minimal disruption to established conventional aircraft traffic and limited voice interactions with the Air Traffic Control (ATC). Early stages of UAM may use existing procedures to safely integrate UAM with conventional flights. This would involve flying under Part 91 Visual Flight Rules (VFR) and using voice for communications. The initial UAM ecosystem will utilize the current infrastructure such as routes, helipads, and ATC services, where practicable. ​A NASA study explored the use of existing helicopter routes in Dallas Fort Worth (DFW) airspace for initial UAM operations with a Letter of Agreement (LOA) that included procedures to request a Class B (controlled airspace) clearance. The research showed that the chosen approach was feasible for near-term, low-demand UAM traffic, but was not scalable. The growth of operations in today’s aviation system has resulted in airspace reorganization and procedures to ensure safety and efficiency as traffic rates increase. One proposed operating innovation that can help with the scalability of UAM is establishing routes and corridors. This may look similar to the Area Navigation (RNAV) procedures used today to streamline operations into busy airports. However, instead of FAA automation systems and ATC managing the flow of traffic, some UAM concepts envision a third-party service provider performing this role as part of the Provider of Services for UAM (PSU) network. The FAA’s UAM ConOps posits that new airspace structures such as UAM corridors include the following design criteria: 1) Minimal impact on existing NAS operations, 2) no or minimal additional ATC services, 3) public interest considerations such as noise, safety, and security, and 4) customer needs. The airspace available in urban environments is limited by the height of buildings, the effect of weather including wind gusts, privacy needs, and a clearance envelope. The new airspace structure would need to be designed around large airports and urban areas where the initial market demand is likely to exist. NASA has started evaluating airspace in the Dallas Fort Worth area to design new airspace structures, keeping the first two design criteria in mind. It is assumed that there will be an on-board pilot-in-command, and the flights will operate under VFR in Visual Meteorological Conditions. Corridors will be required in controlled airspace, whereas UAM operations can fly in uncontrolled Class G and E airspace using current day rules. Keeler et. al identified factors and heuristics for development of routes for UAM operations for integration with airspace close to large airports such as Dallas Fort Worth and Dallas Love Field. This paper describes the heuristics applied to define the corridors, analyzes them with respect to legacy traffic and presents key results.

Urban Air Mobility↗
NASA NTRSDate not supplied

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (AAM) (i.e. urban and rural unmanned aircraft systems) ecosystem, the NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV) to prototype and study the effectiveness AAM capabilities under various operational contexts. HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called the Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with the FMI to identify optimal approaches for displaying information to human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a remotely controlled vehicle completed a takeoff, active flight, and landing sequence while simulated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self- reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users suggested customizable interfaces to accommodate information display preferences, and the ability to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could serve to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

Fleet manager↗
NASA NTRSDate not supplied

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗
DOE OSTI2023

Nanodevice, method of making the same, and method of using the same

A nanodevice provides for electric-field control of magnon-QSD interactions. The nanodevice includes a ferroelectric substrate, a ferromagnetic material disposed over the ferroelectric substrate, and a nanodiamond including an ensemble of nitrogen-vacancy (NV) spins, each NV magnetically interfacing with the ferromagnetic material. An electric field is measured by applying a voltage across the ferroelectric substrate and the ferromagnetic material, changing a magnon excitation spectrum of the ferromagnetic material with respect to an electron spin resonance frequency of the ensemble of NV spins, and measuring a relaxation rate of the ensemble of NV spins.

Shalaev, Vladimir M.↗
DOE OSTI2024

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗
NASA NTRS1998

Distributed Control with Collective Intelligence

We consider systems of interacting reinforcement learning (RL) algorithms that do not work at cross purposes , in that their collective behavior maximizes a global utility function. We call such systems COllective INtelligences (COINs). We present the theory of designing COINs. Then we present experiments validating that theory in the context of two distributed control problems: We show that COINs perform near-optimally in a difficult variant of Arthur's bar problem [Arthur] (and in particular avoid the tragedy of the commons for that problem), and we also illustrate optimal performance in the master-slave problem.

Wolpert, David H.↗
NASA NTRS2003

Basic and Applied Materials Science Research Efforts at MSFC Germane to NASA Goals

Presently, a number of investigations are ongoing that blend basic research with engineering applications in support of NASA goals. These include (1) "Pore Formation and Mobility (PFMI) " An ISS Glovebox Investigation" NASA Selected Project - 400-34-3D; (2) "Interactions Between Rotating Bodies" Center Director's Discretionary Fund (CDDF) Project - 279-62-00-16; (3) "Molybdenum - Rhenium (Mo-Re) Alloys for Nuclear Fuel Containment" TD Collaboration - 800-11-02; (4) "Fabrication of Alumina - Metal Composites for Propulsion Components" ED Collaboration - 090-50-10; (5) "Radiation Shielding for Deep-Space Missions" SD Effort; (6) "Other Research". In brief, "Pore Formation and Mobility" is an experiment to be conducted in the ISS Microgravity Science Glovebox that will systematically investigate the development, movement, and interactions of bubbles (porosity) during the controlled directional solidification of a transparent material. In addition to promoting our general knowledge of porosity physics, this work will serve as a guide to future ISS experiments utilizing metal alloys. "Interactions Between Rotating Bodies" is a CDDF sponsored project that is critically examining, through theory and experiment, claims of "new" physics relating to gravity modification and electric field effects. "Molybdenum - Rhenium Alloys for Nuclear Fuel Containment" is a TD collaboration in support of nuclear propulsion. Mo-Re alloys are being evaluated and developed for nuclear fuel containment. "Fabrication of Alumina - Metal Composites for Propulsion Components" is an ED collaboration with the intent of increasing strength and decreasing weight of metal engine components through the incorporation of nanometer-sized alumina fibers. "Radiation Shielding for Deep-Space Missions" is an SD effort aimed at minimizing the health risk from radiation to human space voyagers; work to date has been primarily programmatic but experiments to develop hydrogen-rich materials for shielding are planned. "Other Research" includes: BUNDLE (Bridgman Unidirectional Dendrite in a Liquid Experiment) activities (primarily crucible development), vibrational float-zone processing (with Vanderbilt University), use of ultrasonics in materials processing (with UAH), rotational effects on microstructural development, and application of magnetic fields for mixing.

Source record↗
DOE OSTI2021

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Abstract Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil–plant–atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
NASA NTRS2005

Online fault adaptive control for efficient resource management in Advanced Life Support Systems

This article presents the design and implementation of a controller scheme for efficient resource management in Advanced Life Support Systems. In the proposed approach, a switching hybrid system model is used to represent the dynamics of the system components and their interactions. The operational specifications for the controller are represented by utility functions, and the corresponding resource management problem is formulated as a safety control problem. The controller is designed as a limited-horizon online supervisory controller that performs a limited forward search on the state-space of the system at each time step, and uses the utility functions to decide on the best action. The feasibility and accuracy of the online algorithm can be assessed at design time. We demonstrate the effectiveness of the scheme by running a set of experiments on the Reverse Osmosis (RO) subsystem of the Water Recovery System (WRS).

NASA Discipline Life Support Systems↗
NASA NTRS2011

Phase-Controlled Magnetic Mirror for Wavefront Correction

Typically, light interacts with matter via the electric field and interaction with weakly bound electrons. In a magnetic mirror, a patterned nanowire is fabricated over a metallic layer with a dielectric layer in between. Oscillation of the electrons in the nanowires in response to the magnetic field of incident photons causes a re-emission of photons and operation as a "magnetic mirror." By controlling the index of refraction in the dielectric layer using a local applied voltage, the phase of the emitted radiation can be controlled. This allows electrical modification of the reflected wavefront, resulting in a deformable mirror that can be used for wavefront control. Certain applications require wavefront quality in the few-nanometer regime, which is a major challenge for optical fabrication and alignment of mirrors or lenses. The use of a deformable magnetic mirror allows for a device with no moving parts that can modify the phase of incident light over many spatial scales, potentially with higher resolution than current approaches. Current deformable mirrors modify the incident wavefront by using nano-actuation of a substrate to physically bend the mirror to a desired shape. The purpose of the innovation is to modify the incident wavefront for the purpose of correction of fabrication and alignment-induced wavefront errors at the system level. The advanced degree of precision required for some applications such as gravity wave detection (LISA - Laser Interferometer Space Antenna) or planet finding (FKSI - Fourier-Kelvin Stellar Interferometer) requires wavefront control at the limits of the current state of the art. All the steps required to fabricate a magnetic mirror have been demonstrated. The modification is to apply a bias voltage to the dielectric layer so as to change the index of refraction and modify the phase of the reflected radiation. Light is reflected off the device and collected by a phase-sensing interferometer. The interferometer determines the initial wavefront of the device and fore optics. A wavefront correction is calculated, and voltage profile for each nanowire strip is determined. The voltage is applied, modifying the local index of refraction of the dielectric under the nanowire strip. This modifies the phase of the reflected light to allow wavefront correction.

Hagopian, John↗