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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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OPTIM generates profile of altitude, airspeed, and flightpath angle as function of range between given set or origin and destination points for particular models of transport aircraft. Profile is optimized in sense of minimizing fuel or time or in minimizing direct operating cost expressed as combination of fuel and time.
Structures capable of deployment into complex, three-dimensional trusses have well known space technology applications such as the support of spacecraft payloads, communications antennas, radar reflectors, and solar concentrators. Such deployable trusses could also be useful in terrestrial applications such as the rapid establishment of structures in military and emergency service situations, in particular with regard to the deployment of enclosures for habitat or storage. To minimize the time required to deploy such an enclosure, a single arch-shaped truss is preferable to multiple straight trusses arranged vertically and horizontally. To further minimize the time required to deploy such an enclosure, a synchronous deployment with a single degree of freedom is also preferable. One method of synchronizing deployment of a truss is the use of a series of gears; this makes the deployment sequence predictable and testable, allows the truss to have a minimal stowage volume, and the deployed structure exhibits the excellent stiffness-to-mass and strength-to-mass ratios characteristic of a truss. A concept for using gears with varying ratios to deploy a truss into a curved shape has been developed and appears to be compatible with both space technology applications as well as potential use in terrestrial applications such as enclosure deployment. As is the case with other deployable trusses, this truss is formed using rigid elements (e.g., composite tubes) along the edges, one set of diagonal elements composed of either cables or folding/hinged rigid members, and the other set of diagonal elements formed by a continuous cable that is tightened by a motor or hand crank in order to deploy the truss. Gears of varying ratios are used to constrain the deployment to a single degree of freedom, making the deployment synchronous, predictable, and repeatable. The relative sizes of the gears and the relative dimensions of the diagonal elements determine the deployed geometry (e.g. curvature) of the truss.
We apply the Squeaky Wheel Optimization (SWO) algorithm to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The problem contains complex constraints relating the feasibility of an astronomical observation to the position and time at which the observation begins, telescope elevation limits, special use airspace, and available fuel. Solving the problem requires making discrete choices (e.g. selection and sequencing of observations) and continuous ones (e.g. takeoff time and setting up observations by repositioning the aircraft). The problem also includes optimization criteria such as maximizing observing time while simultaneously minimizing total flight time. Previous approaches to the problem fail to scale when accounting for all constraints. We describe how to customize SWO to solve this problem, and show that it finds better flight plans, often with less computation time, than previous approaches.
As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or yield additional insights like gradients. The FAST/IOTA facility has been working on implementing and experimentally validating an end-to-end digital twin that is both fast and gradient-aware, allowing for rapid prototyping of new software and experiments with minimal beam time costs. Our framework integrates physics and ML codes for linac and ring simulation through a set of generic interfaces between surrogate and physics-based sections. To reproduce device inputs and outputs, system state is exposed as a deterministic event loop in a specialized discrete event simulator architecture. Because Fermilab is undergoing control system transition, several APIs were implemented as final user interfaces - a fully asynchronous EPICS soft IOC, a gRPC-based Data Pool Manager (DPM), and legacy ACNET protocols. We discuss implementation details as well as challenges handling live data assimilation and future plans to extend modelling to main complex proton accelerators like PIPII and Booster.
As aircraft wings become much more flexible due to the use of light-weight composites material, adverse aerodynamics at off-design performance can result from changes in wing shapes due to aeroelastic deflections. Increased drag, hence increased fuel burn, is a potential consequence. Without means for aeroelastic compensation, the benefit of weight reduction from the use of light-weight material could be offset by less optimal aerodynamic performance at off-design flight conditions. Performance Adaptive Aeroelastic Wing (PAAW) technology can potentially address these technical challenges for future flexible wing transports. PAAW technology leverages multi-disciplinary solutions to maximize the aerodynamic performance payoff of future adaptive wing design, while addressing simultaneously operational constraints that can prevent the optimal aerodynamic performance from being realized. These operational constraints include reduced flutter margins, increased airframe responses to gust and maneuver loads, pilot handling qualities, and ride qualities. All of these constraints while seeking the optimal aerodynamic performance present themselves as a multi-objective flight control problem. The paper presents a multi-objective flight control approach based on a drag-cognizant optimal control method. A concept of virtual control, which was previously introduced, is implemented to address the pair-wise flap motion constraints imposed by the elastomer material. This method is shown to be able to satisfy the constraints. Real-time drag minimization control is considered to be an important consideration for PAAW technology. Drag minimization control has many technical challenges such as sensing and control. An initial outline of a real-time drag minimization control has already been developed and will be further investigated in the future. A simulation study of a multi-objective flight control for a flight path angle command with aeroelastic mode suppression and drag minimization demonstrates the effectiveness of the proposed solution. In-flight structural loads are also an important consideration. As wing flexibility increases, maneuver load and gust load responses can be significant and therefore can pose safety and flight control concerns. In this paper, we will extend the multi-objective flight control framework to include load alleviation control. The study will focus initially on maneuver load minimization control, and then subsequently will address gust load alleviation control in future work.
Domestic hot water temperature maintenance (HWTM) is an important topic in facility management, and there are often opportunities to optimize systems to achieve energy, water, and maintenance savings. The main purpose of an HWTM system is to provide reliable hot water temperature at all fixtures with minimal wait time. This is done by replacing the standby heat losses from hot water sitting idle in pipes during periods of low demand. Traditionally, most commercial buildings do this by having water recirculate back to the water heater to be reheated. Other currently available HWTM systems are also discussed in this resource. HWTM systems can help maintain water at appropriate temperatures, minimize heat loss, and minimize delivery times to fixtures to improve the function of a building. This webpage includes a summary of HWTM options along with important considerations regarding occupant safety and comfort, and maintenance strategies for optimal and efficient operations. Domestic hot water (DHW) generation systems are referred to but are not the focus of this resource.
Wire-arc additive manufacturing (WAAM) has become a cost-efficient metal additive manufacturing process. However, depositing aluminum with WAAM is challenging due to its sensitivity to heat input (linear energy density), which can cause undesirable surface topology waviness if not controlled. Thus, a process window is needed that can produce stable geometry and deposition conditions while minimizing production times. In this study, 5183 aluminum alloy wire is used to deposit 10-layer walls with varying wire feed speeds (WFS) and traverse speeds (TS) (at a constant WFS/TS ratio) and varying interpass temperature (IPT). In-situ process data consisting of optical contact-tip-workpiece-distance (CTWD) and current/voltage measurements are collected to determine process condition stability throughout the build. Part geometry is measured using a 3D scanner and build porosity is characterized via digital X-ray. A process window is identified that produces stable surface topology and process conditions at a minimal production time.
Classical and minimax optimal control problems arising in the study of aeroassisted coplanar orbit transfer from a high planetary orbit to a low one are considered. Attention is given to (1) the minimization of the energy required for the maneuver; (2) minimization of the time integral of the heating rate; (3) minimization of the time of flight during the atmospheric portion of the trajectory; (4) maximization of the time of flight during the atmospheric portion of the trajectory; (5) minimization of the time integral of the path inclination; and (6) minimization of the sum of the squares of the entry and exit path inclinations.
In this paper, we propose a framework called FPDeep, which uses a hybrid of model and layer paral- lelism to configure distributed reconfigurable clusters to train DNNs. This approach has numerous benefits. First, the design does not suffer from batch size growth. Second, novel workload and weight partitioning leads to balanced loads of both among nodes. And third, the entire system is fine-grained pipeline. This leads to high parallelism and utilization and also minimizes the time features need to be cached while waiting for back-propagation.
Our research explores innovative solutions to address the challenge of battery disruptions in electric vehicles (EVs) on highways. We propose a centralized fleet ownership model where a company manages a fleet of Mobile Charging Drones (MCDs) guided by a k-VRP (Vehicle Routing Problem) framework. This model is designed to tackle a multi-objective optimization issue with three primary goals: reduction of the overall operating costs, decrease in the cumulative waiting time, and minimization of the combined operating costs and waiting times. This approach extends beyond the usual VRP constraints, encompassing specific limitations for both MCDs and disrupted EVs (DEVs). Additionally, our study delves into the concept of decentralized fleet ownership through the lens of crowdsourcing. Preliminary numerical analyses indicate that the capital cost of MCDs is a significant factor on the charging service, and the system performance is sensitive to DEV owner's value of time (VOT) when VOTs are relatively low.
This Paper is a case study of the development and execution of the End-of-Mission plans for the Earth Radiation Budget Satellite (ERBS) and the Upper Atmosphere Research Satellite (UARS). The goals of the End-of-Mission Plans are to minimize the time the spacecraft remains on orbit and to minimize the risk of creating orbital debris. Both of these Missions predate the NASA Management Instructions (NMI) that directs missions to provide for safe mission termination. Each spacecrafts had their own unique challenges, which required assessing End-of-Mission requirements versus spacecraft limitations. Ultimately the End-of- Mission operations were about risk mitigation. This paper will describe the operational challenges and the lessons learned executing these End-of-Mission Plans
Safeguards against toxic chemical exposures during manned Mars missions (MMMs) will be important for the maintenance of crew health and the accomplishment of mission objectives. Potential sources include offgassing, thermodegradation or combustion of materials, metabolic products of crew members, and escape of chemical from containment. Spacecraft maximum allowable concentration (SMAC) limits will have to be established for potential contaminants during the MMMs. The following factors will be used in establishing these limits: duration of mission, simultaneous exposure to other contaminants, deconditioning of crew members after long periods of reduced gravity, and simultaneous exposure to ionizing radiation. Atmospheric contaminant levels in all compartments of the transit spacecraft and Manned Mars Station (MMS) will be monitored at frequent intervals with a real time analyzer. This analyzer will be highly automated, requiring minimal crew time and expertise. The atmospheric analyzer will find other usages during the MMMs such as analyzing Martian atmospheres and soils, exhaled breath and body fluids of crew members, and reaction products in chemical processing facilities.
The proposed U.S. High Speed Civil Transport (HSCT) will revolutionize commercial air travel by providing economical supersonic passenger service to destinations worldwide. Unlike the high-bypass turbofan engines that propel today's subsonic airliners, HSCT engines will have much higher jet exhaust speeds. Jet noise, caused by the turbulent mixing of high-speed exhaust with the surrounding air, poses a significant challenge for HSCT engine designers. To resolve this challenge, engineers have designed advanced mixer rejector nozzles that reduce HSCT jet noise to airport noise certification levels by entraining and mixing large quantities of ambient air with the engines' jet streams. Although this works well during the first several minutes of flight, far away from the airport, as the HSCT gains speed and climbs, poor ejector inlet recovery and ejector ram drag contribute to poor thrust, making it advantageous to turn off the ejector. Doing so prematurely, however, can cause unacceptable noise levels to propagate to the ground, even when the aircraft is many miles from the airport. This situation lends itself ideally to optimization, where the aircraft trajectory, throttle setting, and ejector setting can be varied (subject to practical aircraft constraints) to minimize the noise propagated to the ground. A method was developed at the NASA Lewis Research Center that employs a variation of the classic energy state approximation: a trajectory analysis technique historically used to minimize climb time or fuel burned in many aircraft problems. To minimize the noise on the ground at any given throttle setting, high aircraft altitudes are desirable; but the HSCT may either climb quickly to high altitudes using a high, noisy throttle setting or climb more slowly at a lower, quieter throttle setting. An optimizer has been programmed into NASA's existing aircraft and noise analysis codes to balance these options by dynamically choosing the best altitude-velocity path and throttle setting history. The noise level standard, or metric, used in the optimizer should be one that accurately reflects the subjective annoyance levels of ground-based observers under the flight path. A variety of noise metrics are available, many of which are practical for airport-vicinity noise certification. Unlike airport noise, however, the HSCT's climb noise will be characterized by relatively low noise levels, long durations, and low-frequency spectra. The noise metrics used in these calculations are based on the recommendations of researchers at the NASA Langley Research Center, who have correlated the flyover noise annoyance levels of actual laboratory subjects with a variety of measurements. Analysis of data from this optimizer has shown that significant reductions in noise may be obtained with trajectory optimization. And since throttling operations are performed in the subsonic portion of the climb path (where thrust is plentiful), only small penalties in HSCT range or fuel performance occur.
Significant advances have been made to non-intrusive flow field diagnostics in the past decade. Camera based techniques are now capable of determining physical qualities such as surface deformation, surface pressure and temperature, flow velocities, and molecular species concentration. In each case, extracting the pertinent information from the large volume of acquired data requires powerful and efficient data visualization tools. The additional requirement for real time visualization is fueled by an increased emphasis on minimizing test time in expensive facilities. This paper will address a capability titled LiveView3D, which is the first step in the development phase of an in depth, real time data visualization and analysis tool for use in aerospace testing facilities.
The Fastener Capture Plate technology was developed to solve the problem of capturing loose hardware and small fasteners, items that were not originally intended to be disengaged in microgravity, thus preventing them from becoming space debris. This technology was incorporated into astronaut tools designed and successfully used on NASA s Hubble Space Telescope Servicing Mission #4. The technology s ultimate benefit is that it allows a very time-efficient method for disengaging fasteners and removing hardware while minimizing the chances of losing parts or generating debris. The technology aims to simplify the manual labor required of the operator. It does so by optimizing visibility and access to the work site and minimizing the operator's need to be concerned with debris while performing the operations. It has a range of unique features that were developed to minimize task time, as well as maximize the ease and confidence of the astronaut operator. This paper describes the technology and the astronaut tools developed specifically for a complicated on-orbit repair, and it includes photographs of the hardware being used in outer space.
This Component-Level Electronic-Assembly Repair (CLEAR) Operational Concept document was developed as a first step in developing the Component-Level Electronic-Assembly Repair (CLEAR) System Architecture (NASA/TM-2011-216956). The CLEAR operational concept defines how the system will be used by the Constellation Program and what needs it meets. The document creates scenarios for major elements of the CLEAR architecture. These scenarios are generic enough to apply to near-Earth, Moon, and Mars missions. The CLEAR operational concept involves basic assumptions about the overall program architecture and interactions with the CLEAR system architecture. The assumptions include spacecraft and operational constraints for near-Earth orbit, Moon, and Mars missions. This document addresses an incremental development strategy where capabilities evolve over time, but it is structured to prevent obsolescence. The approach minimizes flight hardware by exploiting Internet-like telecommunications that enables CLEAR capabilities to remain on Earth and to be uplinked as needed. To minimize crew time and operational cost, CLEAR exploits offline development and validation to support online teleoperations. Operational concept scenarios are developed for diagnostics, repair, and functional test operations. Many of the supporting functions defined in these operational scenarios are further defined as technologies in NASA/TM-2011-216956.
This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.
In this study, we have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale additive manufacturing (AM) via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreement with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation.