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At least 109 records · Page 6

Solar Sail Propulsion Technology at NASA

NASA's In-Space Propulsion Technology Program developed the first generation of solar sail propulsion systems sufficient to accomplish inner solar system science and exploration missions. These first generation solar sails, when operational, will range in size from 40 meters to well over 100 meters in diameter and have an area density of less than 13 grams per square meter. A rigorous, multi-year technology development effort culminated in 2005 with the testing of two different 20-m solar sail systems under thermal vacuum conditions. This effort provided a number of significant insights into the optimal design and expected performance of solar sails as well as an understanding of the methods and costs of building and using them. In addition, solar sail orbital analysis tools for mission design were developed and tested. Laboratory simulations of the effects of long-term space radiation exposure were also conducted on two candidate solar sail materials. Detailed radiation and charging environments were defined for mission trajectories outside the protection of the earth's magnetosphere, in the solar wind environment. These were used in other analytical tools to prove the adequacy of sail design features for accommodating the harsh space environment. The presentation will describe the status of solar sail propulsion within NASA, near-term solar sail mission applications, and near-term plans for further development.

Johnson, Charles Les↗

Grayscale Optical Correlator Workbench

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

Hanan, Jay↗

X-Ray Imaging Study

The space environment in which the Space Station Freedom and other space platforms will orbit is truly a hostile environment. For example, the currently estimated integral fluence for electrons above 1 Mev at 2000 nautical miles is above 2 x 1O(exp 10) electrons/sq cm/day and the proton integral fluence is above 1 x 10(exp 9) protons/sq cm/day. At the 200 - 400 nautical miles, which is more representative of the altitude which will provide the environment for the Space Station, each of these fluences will be proportionally less; however, the data indicates that the radiation environment will obviously have an effect on structural materials exposed to the environment for long durations. The effects of this combined environment is the issue which needs to be understood for the long term exposure of structures in space. At the same time, there will be substantial potential for collisions between the space platforms and space debris. The current NASA catalogue contains over 4500 objects floating in space which are not considered payloads. This debris can have significant effects on collision with orbiting spacecraft. In order to better understand the effect of these hostile phenomena on spacecraft, several types of studies are being performed to simulate at some level the effect of the environment. In particular the study of debris clouds produced by hypervelocity impact on the various surfaces anticipated on the Space Station is very important at this point in time. The need to assess the threat of such debris clouds on space structures is an on-going activity. The Space Debris Impact facility in Building 4612 provides a test facility to monitor the types of damage produced with hypervelocity impact. These facilities are used to simulate space environmental effects from energetic particles. Flash radiography or x-ray imaging has traditionally provided such information and as such has been an important tool for recording damage in situ with the event. The proper operation of the system can provide much useful information with respect to parametric analysis of the hypervelocity experiment. The following report outlines the procedures developed to optimize the operation of the x-ray imaging system and its operational characteristics.

OBrien, Susan K.↗

Microhard MHX 2420 Orbital Performance Evaluation Using RT Logic T400CS

A major upfront cost of building low cost Nanosatellites is the communications sub-system. Most radios built for space missions cost over $4,000 per unit. This exceeds many budgets. One possible cost effective solution is the Microhard MHX2420, a commercial off-the-shelf transceiver with a unit cost under $1000. This paper aims to support the Nanosatellite community seeking an inexpensive radio by characterizing Microhard's performance envelope. Though not intended for space operations, the ability to test edge cases and increase average data transfer speeds through optimization positions this radio as a solution for Nanosatellite communications by expanding usage to include more missions. The second objective of this paper is to test and verify the optimal radio settings for the most common cases to improve downlinking. All tests were conducted with the aid of the RT Logic T400CS, a hardware-in-the-loop channel simulator designed to emulate real-world radio frequency (RF) link effects. This study provides recommended settings to optimize the downlink speed as well as the environmental parameters that cause the link to fail.

Microhard MHX 2420↗

Deriving a Suite of Climate Data Records from 21-years of Sounder Observations

Two retrieval algorithms, a Single Field-of-view Sounder Atmospheric Product (SiFSAP) Level 2 algorithm and a Climate Fingerprinting Sounder Product (ClimFiSP) Level 3 algorithm, have been developed at NASA Langley Research Center. In this presentation, we will demonstrate the radiance closure build into these two algorithms. This is possible due to the use of a principal-component-based radiative transfer model (PCRTM). The PCRTM enables the inclusion of all available spectral information from hyperspectral IR sounders. It also has fast and accurate capability of modeling observed cloudy radiance spectra directly. The SiFSAP, which fits sounder radiance spectra using PCRTM as forward model and an optimal estimation as inverse model, has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. With great support from NASA sounder SIPS, the SiFSAP algorithm has been delivered to NASA GES DISC for L2 and L3 data generation and releasing. The ClimFiSP uses a spectral fingerprinting method to directly generate L3 data products from spatiotemporally averaged L1 data. The goal of ClimFiSP is to generate high-quality climate data records (CDRs) from multiple IR sounders (e.g. Aqua AIRS, SNPP CrIS, NOAA-20 and NOAA-21 CrIS) using a consistent retrieval methodology. Using CHIRP L1 data, we have generated 20-years of CDRs for atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties. The algorithm will be transitioned to Sounder SIPS soon and eventually to NASA GES DISC.

Xu Liu↗

Autonomy Verification & Validation Roadmap and Vision 2045

Advanced capabilities planned for the next generation of autonomous and increasingly autonomous air vehicles will include non-traditional components based on artificial intelligence, machine learning, and complex optimization and planning algorithms. These complex components will be used to provide enhanced safety and high-level decision-making functions. However, there are serious barriers to the deployment of autonomous aircraft in the National Airspace System (NAS). Current civil aviation certification processes are based on the concept that the correct behavior of a system or a component must be completely specified and verified prior to operation. This report from the Autonomy Verification and Validation (V&V) Roadmap and Vision 2045 project presents the most recent effort to build a comprehensive list of verification challenges and needs for autonomous aircraft, a roadmap to meet those autonomy V&V needs, the services they can enable, and point to the certification gaps they fill. To accomplish these goals, we assembled a team of world-class researchers from the aerospace industry (Boeing, Collins Aerospace, and GeneralElectric) and academia (University of Michigan, University of Texas, and Massachusetts Institute of Technology) with deep expertise in autonomy, aerospace systems, and assurance of Artificial Intelligence/machine learning systems.

Software Assurance↗

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗

Production and Characterization of Additively Manufactured Radiator Panels with Integral Branching Heat Pipes for High-Temperature Heat Rejection

Emerging concepts for fission surface power and nuclear electric propulsion necessitate lightweight, mechanically robust, and thermally efficient heat rejection radiators. State-of-the-art intermediate-temperature (~400 K) composite radiator assemblies have been developed based on titanium-water heat pipes bonded to metal, graphite, and carbon-fiber-based panels. NASA has identified a need for new radiator concepts that can operate at even higher temperatures (500 – 600 K), minimize thermal resistances and thermal stress failures at bond interfaces, and approach areal densities of 2 – 3 kg m -2 . To meet these needs, our team is developing additively manufactured (AM) radiator panels with integral branching wicking heat pipe networks. Water is selected as the working fluid for this temperature range. Based on simulations and thermal vacuum experiments, these branching embedded heat pipe networks can efficiently distribute heat over panels for finned surface efficiencies of η f >70% at T H = 500 K input heat. This paper first presents laser powder-bed fusion AM strategies to produce embedded porous structures for wicking heat pipes in Inconel 718 and titanium alloys (commercially pure and Ti-6Al-4V alloys). Post-build chemical and thermal treatments are described that yield hydrophilic wicking surfaces for operation with water. Transient rate-of-rise experiments with water and acetone are reported that yield estimates for AM wick porosity (ϵ), permeability (K), and effective pore radius (r pore ). Based on the wick characterization results, small prototype radiator panels (75 × 125 mm) with integrated heat pipe networks were manufactured. Heat rejection performance data are presented from cold thermal vacuum testing, with heat input temperatures up to ~510 K. Future efforts will focus on improving heat pipe performance, optimizing radiator mass, and evaluating larger panels to assess scalability.

thermal management↗

Production and Characterization of Additively Manufactured Radiator Panels With Integral Branching Heat Pipes for High-Temperature Heat Rejection

Emerging concepts for fission surface power and nuclear electric propulsion necessitate lightweight, mechanically robust, and thermally efficient heat rejection radiators. State-of-the-art intermediate-temperature (~400 K) composite radiator assemblies have been developed based on titanium-water heat pipes bonded to metal, graphite, and carbon-fiber-based panels. NASA has identified a need for new radiator concepts that can operate at even higher temperatures (500 – 600 K), minimize thermal resistances and thermal stress failures at bond interfaces, and approach areal densities of 2 – 3 kg m -2 . To meet these needs, our team is developing additively manufactured (AM) radiator panels with integral branching wicking heat pipe networks. Water is selected as the working fluid for this temperature range. Based on simulations and thermal vacuum experiments, these branching embedded heat pipe networks can efficiently distribute heat over panels for finned surface efficiencies of η f >70% at T H = 500 K input heat. This paper first presents laser powder-bed fusion AM strategies to produce embedded porous structures for wicking heat pipes in Inconel 718 and titanium alloys (commercially pure and Ti-6Al-4V alloys). Post-build chemical and thermal treatments are described that yield hydrophilic wicking surfaces for operation with water. Transient rate-of-rise experiments with water and acetone are reported that yield estimates for AM wick porosity (ϵ), permeability (K), and effective pore radius ( r pore ). Based on the wick characterization results, small prototype radiator panels (75 × 125 mm) with integrated heat pipe networks were manufactured. Heat rejection performance data are presented from cold thermal vacuum testing, with heat input temperatures up to ~510 K. Future efforts will focus on improving heat pipe performance, optimizing radiator mass, and evaluating larger panels to assess scalability.

nuclear electric propulsion↗

Hardware Autonomy for Space Infrastructure

NASA prioritizes autonomous systems development with the expectation that it will continue to drive significant improvements in human and science exploration capability. Crew operations benefit from a spectrum of machine assistance to complete replacement of dangerous or highly repetitive tasks. Many science operations have a teleoperation component, and similarly benefit from a range of autonomy implementations that make long distance applications feasible. As we consider longer duration deep space missions, we also consider higher levels of autonomy in order meet emergent safety, maintenance, and logistics needs. One of the challenges within this scope is installation and maintenance of infrastructure, such as large scale instrumentation and communications equipment, crew habitats, and operational facilities. We describe how a programmable meta-material architecture may shift the paradigm of how we design, build, and operate future space infrastructure and assets. A primary objective of this strategy is to free the design space from launch vehicle constraints and fundamentally shift how a mission is designed and conducted. This integrates advances in materials (mechanical meta-materials), manufacturing (cooperative mobile robotics), and autonomy (multi-agent planning algorithms). Engineering systems that utilize a modular and reconfiguration building block approach, such as digital communication and computation systems, currently lead in terms of size and complexity scalability. NASA is extending the benefits and flexibility of digital systems to hardware systems, to optimize materials life-cycle management and expand our space exploration mission capabilities to meet long duration and deep space infrastructure needs, in accordance with long term NASA goals of "in-space reliance" and "mass-less exploration."

In space assembly↗

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗

Development Unit for In-Space Pneumatic Helium Transfer Compressor

High-pressure gaseous helium (GHe) plays a critical role in spacecraft propulsion due to its near exclusive use for pressurization of propellant tanks. Several different designs for helium compressor technologies have been developed for use on Earth; however, significant design changes are required to meet the power, thermal/heat dissipation, vacuum, vibration/shock, size, mass, and efficiency requirements needed for space and launch environments. Currently, no capability exists for mass efficient on-orbit GHe (or xenon) transfer, nor has it ever been attempted. This effort proposed several challenging requirements for the vendor to develop a one-of-a-kind pneumatic compressor prototype. In order to develop a compressor prototype at a TRL 4, a partnership with Air Squared, Inc. was established. This CIF project concluded with the receipt of a prototype along with a proposed design for a flight unit; however, it will not be built due to funding limitations. The vendor had moderate success with initial testing of the prototype at lower pressures (with shimming configured for low pressure). There were delays with testing since the unit was built for higher pressures and the low pressure shimming was challenging to implement. It was found that operation of the compressor at lower pressures caused increased friction on the motor shaft which resulted in the unit drawing more power (current). This was initially thought to be a motor or controller defect. Subsequent high pressure testing at KSC showed that the friction was reduced for the optimal design point (with a high pressure shimming configuration) and the motor (and controller) performed nominally. Following the vendor testing, the unit was tuned/shimmed for a nominal inlet pressure and shipped to KSC for high pressure testing using the custom-designed setup in the Vehicle Assembly Building. The unit performed well, showing the capability to achieve over higher pressure of compression. The pressure differential could likely increase, however, the maximum output of the power supply used for testing was reached, limiting the compressor motor’s capability. Following the GN2 testing, the test setup was converted to GHe with at high pressure. It was shown that although the unit was unable to achieve similar high pressure differentials due to reverse leakage of the GHe through the scroll tip seals, it did achieve the desired GHe compression. This may still be useful for some applications, however, for the purpose of on-orbit GHe transfer, the single stage design would need to be changed to include multiple stages to achieve the compression goals initially proposed by the project.

Brian Nufer↗

Analytical Modeling of Planetary Excavation for in Situ Resource Utilization

The space-faring capabilities of humans are dependent on the ability to interact with plan-etary surfaces safely and efficiently and utilize local re-sources. Since planetary regolith will be the primary feedstock for in situ resource utilization (ISRU) and infrastructure development activities [1,2], the site-specific geomechanical properties must be understood to optimize excavation operations [3]. Excavating planetary regolith is challenging due to its unique geomechanical properties, 1/6th G reduced gravity extreme conditions, and limited energy resources. Therefore, it is critical to develop technologies that reduce excavation force requirements and minimize tool path inefficiencies to save time and energy during planetary re-source acquisition and infrastructure development [3]. There have been several experimental investigations of methods to optimize planetary excavations [4,5], but none developed predictive capabilities. This abstract presents a simple analytical method that will be used to model laboratory and mission excavation data. Future work will build on the simple analytical method here to include high-fidelity numerical simulations of planetary excavation mechanics.

Regolith↗

Advances in Modeling Solar System Internet Structures and their Data Flows

With an ever-increasing presence in space, there is also an increasing burden on existing communications infrastructure. We are heading towards an inflection point where the traditional approach of scheduled, single-path communications for space will no longer be viable. One answer is Delay Tolerant Networking (DTN), which takes the once disparate system of point-to-point links and unifies them in a networked architecture, thereby making communications more scalable. However, much work remains for discovering and harnessing the underlying theory of DTN. For example, in the terrestrial setting the interplay between routing domains is well-understood, however this is not the case in DTNs. In this paper, we build up the fundamental foundations of DTN, with an emphasis on modeling time varying networks and data flows across them, with examples of cross-domain routing in a DTN. A lofty goal of DTN is to enable the so-called Solar System Internet (SSI), which implies a standardized and robust suite of protocols. These protocols include routing across disconnected networks using store, carry, and forward mechanisms, which is necessary due to the disconnections, delays, and mobility intrinsic to space networks. Due to these factors, each of which generalize traditional networking, there is a deep and rich theory of DTNs. Here we build off of past successes to broaden this theory while striving to keep actionable results a goal for future implementations and operations. The approach includes modeling the unicast, broadcast, and multicast communications using the language of hypergraphs, which capture the geometric properties of such networked communications algebraically. Also inherent to these networks is their time-varying nature, particularly given mobility, and hence we also cultivate modeling techniques that respect this time dependence. This leads us to develop models using tools from category theory and algebraic geometry, which provide a language well-suited to describing synchronization and optimization over such networks. We also introduce and study a novel generalization of curvature applicable to time-evolving networks, which provides quantitative controls on diffusion processes on the network. Because an interplanetary network would feature links with propagation delays the preclude discovery (feedback) mechanisms, they will always feature a scheduled component. However, it is beneficial to support discovery where possible. While DTNs do not yet have strong definitions for their analogues of autonomous systems or network areas, we show how to join dynamic and schedule-based routing domains, using the language of sheaves, which marks progress towards such definitions. We conclude with a discussion of the progress made, as well as suggestions for future work.

Delay Tolerant Networking↗

A perspective on future directions in aerospace propulsion system simulation

The design and development of aircraft engines is a lengthy and costly process using today's methodology. This is due, in large measure, to the fact that present methods rely heavily on experimental testing to verify the operability, performance, and structural integrity of components and systems. The potential exists for achieving significant speedups in the propulsion development process through increased use of computational techniques for simulation, analysis, and optimization. This paper outlines the concept and technology requirements for a Numerical Propulsion Simulation System (NPSS) that would provide capabilities to do interactive, multidisciplinary simulations of complete propulsion systems. By combining high performance computing hardware and software with state-of-the-art propulsion system models, the NPSS will permit the rapid calculation, assessment, and optimization of subcomponent, component, and system performance, durability, reliability and weight-before committing to building hardware.

Miller, Brent A.↗

Simulating Operations at a Spaceport

SPACESIM is a computer program for detailed simulation of operations at a spaceport. SPACESIM is being developed to greatly improve existing spaceports and to aid in designing, building, and operating future spaceports, given that there is a worldwide trend in spaceport operations from very expensive, research- oriented launches to more frequent commercial launches. From an operational perspective, future spaceports are expected to resemble current airports and seaports, for which it is necessary to resolve issues of safety, security, efficient movement of machinery and people, cost effectiveness, timeliness, and maximizing effectiveness in utilization of resources. Simulations can be performed, for example, to (1) simultaneously analyze launches of reusable and expendable rockets and identify bottlenecks arising from competition for limited resources or (2) perform what-if scenario analyses to identify optimal scenarios prior to making large capital investments. SPACESIM includes an object-oriented discrete-event-simulation engine. (Discrete- event simulation has been used to assess processes at modern seaports.) The simulation engine is built upon the Java programming language for maximum portability. Extensible Markup Language (XML) is used for storage of data to enable industry-standard interchange of data with other software. A graphical user interface facilitates creation of scenarios and analysis of data.

Nevins, Michael R.↗

Thermodynamic Vent System for an On-Orbit Cryogenic Reaction Control Engine

A report discusses a cryogenic reaction control system (RCS) that integrates a Joule-Thompson (JT) device (expansion valve) and thermodynamic vent system (TVS) with a cryogenic distribution system to allow fine control of the propellant quality (subcooled liquid) during operation of the device. It enables zero-venting when coupled with an RCS engine. The proper attachment locations and sizing of the orifice are required with the propellant distribution line to facilitate line conditioning. During operations, system instrumentation was strategically installed along the distribution/TVS line assembly, and temperature control bands were identified. A sub-scale run tank, full-scale distribution line, open-loop TVS, and a combination of procured and custom-fabricated cryogenic components were used in the cryogenic RCS build-up. Simulated on-orbit activation and thruster firing profiles were performed to quantify system heat gain and evaluate the TVS s capability to maintain the required propellant conditions at the inlet to the engine valves. Test data determined that a small control valve, such as a piezoelectric, is optimal to provide continuously the required thermal control. The data obtained from testing has also assisted with the development of fluid and thermal models of an RCS to refine integrated cryogenic propulsion system designs. This system allows a liquid oxygenbased main propulsion and reaction control system for a spacecraft, which improves performance, safety, and cost over conventional hypergolic systems due to higher performance, use of nontoxic propellants, potential for integration with life support and power subsystems, and compatibility with in-situ produced propellants.

Hurlbert, Eric A.↗

Multi-point Adjoint-Based Design of Tilt-Rotors in a Noninertial Reference Frame

Optimization of tilt-rotor systems requires the consideration of performance at multiple design points. In the current study, an adjoint-based optimization of a tilt-rotor blade is considered. The optimization seeks to simultaneously maximize the rotorcraft figure of merit in hover and the propulsive efficiency in airplane-mode for a tilt-rotor system. The design is subject to minimum thrust constraints imposed at each design point. The rotor flowfields at each design point are cast as steady-state problems in a noninertial reference frame. Geometric design variables used in the study to control blade shape include: thickness, camber, twist, and taper represented by as many as 123 separate design variables. Performance weighting of each operational mode is considered in the formulation of the composite objective function, and a build up of increasing geometric degrees of freedom is used to isolate the impact of selected design variables. In all cases considered, the resulting designs successfully increase both the hover figure of merit and the airplane-mode propulsive efficiency for a rotor designed with classical techniques.

Jones, William T.↗