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Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment.
Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.
This report describes the improvements and enhancements to a neural network based approach for directly adapting to aerodynamic changes resulting from damage or failures. This research is a follow-on effort to flight tests performed on the NASA F-15 aircraft as part of the Intelligent Flight Control System research effort. Previous flight test results demonstrated the potential for performance improvement under destabilizing damage conditions. Little or no improvement was provided under simulated control surface failures, however, and the adaptive system was prone to pilot-induced oscillations. An improved controller was designed to reduce the occurrence of pilot-induced oscillations and increase robustness to failures in general. This report presents an analysis of the neural networks used in the previous flight test, the improved adaptive controller, and the baseline case with no adaptation. Flight test results demonstrate significant improvement in performance by using the new adaptive controller compared with the previous adaptive system and the baseline system for control surface failures.
This article summarizes the capabilities and development of the Helios version 2.0, or Shasta, software for rotary wing simulations. Specific capabilities enabled by Shasta include off-body adaptive mesh refinement and the ability to handle multiple interacting rotorcraft components such as the fuselage, rotors, flaps and stores. In addition, a new run-mode to handle maneuvering flight has been added. Fundamental changes of the Helios interfaces have been introduced to streamline the integration of these capabilities. Various modifications have also been carried out in the underlying modules for near-body solution, off-body solution, domain connectivity, rotor fluid structure interface and comprehensive analysis to accommodate these interfaces and to enhance operational robustness and efficiency. Results are presented to demonstrate the mesh adaptation features of the software for the NACA0015 wing, TRAM rotor in hover and the UH-60A in forward flight.
The Ames Engineering Directorate is the principal engineering organization supporting aerospace systems and spaceflight projects at NASA's Ames Research Center in California's Silicon Valley. The Directorate supports all phases of engineering and project management for flight and mission projects-from R&D to Close-out-by leveraging the capabilities of multiple divisions and facilities.The Mission Design Center (MDC) has full end-to-end mission design capability with sophisticated analysis and simulation tools in a collaborative concurrent design environment. Services include concept maturity level (CML) maturation, spacecraft design and trades, scientific instruments selection, feasibility assessments, and proposal support and partnerships. The Engineering Systems Division provides robust project management support as well as systems engineering, mechanical and electrical analysis and design, technical authority and project integration support to a variety of programs and projects across NASA centers. The Applied Manufacturing Division turns abstract ideas into tangible hardware for aeronautics, spaceflight and science applications, specializing in fabrication methods and management of complex fabrication projects. The Engineering Evaluation Lab (EEL) provides full satellite or payload environmental testing services including vibration, temperature, humidity, immersion, pressure/altitude, vacuum, high G centrifuge, shock impact testing and the Flight Processing Center (FPC), which includes cleanrooms, bonded stores and flight preparation resources. The Multi-Mission Operations Center (MMOC) is composed of the facilities, networks, IT equipment, software and support services needed by flight projects to effectively and efficiently perform all mission functions, including planning, scheduling, command, telemetry processing and science analysis.
Problem Statement: Develop robust CFD-based methods for rapid design and analysis of supersonic cruise aircraft that are highly efficient, and have a low sonic boom. What is our approach? - Advanced Efficient Analysis / Design Methods - Develop computational algorithms and techniques for rapid high fidelity analysis of supersonic fluid flow phenomena, which will also contribute to multi-fidelity analysis / design tools. - Experimental Validation - Validate concepts for design optimization of both high aerodynamic efficiency and low sonic boom.
We present the discovery of two nearly identically sized sub-Neptune transiting planets orbiting HD 63935, abright(V=8.6 mag), Sun-like(Teff=5560 K)star at 49 pc. TESS identified thefirst planet, HD 63935 b(TOI-509.01), in Sectors 7 and 34. We identified the second signal(HD 63935 c)in Keck High Resolution EchelleSpectrometer and Lick Automated Planet Finder radial velocity data as part of our follow-up campaign. It wassubsequently confirmed with TESS photometry in Sector 34 as TOI-509.02. Our analysis of the photometric andradial velocity data yielded a robust detection of both planets with periods of 9.0600±0.007 and 21.40±0.0019days, radii of 2.99±0.14 and 2.90±0.13R⊕, and masses of 10.8±1.8 and 11.1±2.4M⊕. We calculated densities for planets b and c consistent with a few percent of the planet mass in hydrogen/helium envelopes. Wealso describe our survey’s efforts to choose the best targets for James Webb Space Telescope atmospheric follow-up. These efforts suggest that HD 63935 b has the most clearly visible atmosphere of its class. It is the best targetfor transmission spectroscopy(ranked by the transmission spectroscopy metric, a proxy for atmosphericobservability)in the so far uncharacterized parameter space comprising sub-Neptune-sized(2.6R⊕<Rp<4R⊕),moderately irradiated(100F⊕<Fp<1000F⊕)planets around G stars. Planet c is also a viable target fortransmission spectroscopy, and given the indistinguishable masses and radii of the two planets, the system servesas a natural laboratory for examining the processes that shape the evolution of sub-Neptune planets.
The Decadal Survey report released [1] prioritizes Uranus as the highest priority Flagship class mission to be explored with an orbiter and a probe and it also recommended Saturn Probe under New Frontiers mission class. Thermal protection system (TPS) is essential for Uranus and Saturn probe missions. The two cardinal requirements are that it must be fail-safe and yet be mass efficient. The Decadal Survey report also pointed out the readiness of heatshield for extreme entry environment technology (HEEET) at TRL 6 for probe missions at Gas Giants. HEEET relies on 3-D weaving and is shown to be a robust and mass efficient TPS through ground testing and analysis. HEEET was matured to TRL 6 in 2019. HEEET was reported at the Ice Giant Workshop in 2019 at Marseille. Since 2019, significant advances have been made primarily because of Mars Sample Return (MSR) mission. MSR baselined 3-D Woven TPS as its heatshield for the earth entry system. MSR earth entry system (EES) requirements and the resulting heatshield/TPS requirements are most stringent of all entry missions. This is a result of backward contamination protection which classifies MSR as a “restricted class 5” mission to safeguard the accidental release of potentially hazardous Mars Sample into Earth’s atmosphere. Complex requirements for the heatshield start with micro-meteor impact tolerance followed by the requirement for steep entry to minimize the size of the impact footprint which results in extreme heating. The heatshield is part of the impact attenuation system. The EES architecture does not use a parachute and is designed to tolerate impact loads. Hence heatshield TPS selection and design becomes one of the key challenges. After completion of the HEEET technology maturation in 2019, IRAD efforts focused on assessing the 3-D Woven family of TPS to MSR EES. After nearly two years of evaluation of alternate TPS such as carbon phenolic, C-C hot structure, PICA, and 3-D woven family of TPS, a single layer 3-D woven TPS derived from the dual-layer HEEET was down selected and is currently the baseline. A new loom capable of weaving the single-layer 3-D woven preform at 80” wide has been designed, assembled and is currently on the verge of weaving the MSR EES TPS. During the HEEET maturation and the follow-on development, the single-layer TPS has been tested at extreme heating conditions. As a result, single layer TPS was recommended and evaluated during the Planetary Mission Concept Studies funded by NASA in preparation for the Decadal committee. In addition, in anticipation of Saturn mission proposals, single layer was evaluated as well. Aerocapture can reduce the trip time, also allow bigger payload fraction and in addition, it allows for the possibility of probe delivery once the spacecraft is in orbit. This can lead to obtaining both in-situ data as well as data from orbit simultaneously. Since Aerocapture depletes energy/velocity, probe delivery from orbit reduces the demand on TPS. Aerocapture was mentioned in the Decadal Study report as ready for implementation, but due to perceived risk it is not adopted by the mission designers. Establishing TPS readiness for aerocapture missions will be addressed. Going one step beyond aerocapture is aerogravity assist if fast return is the goal. Recent studies [4] looked at aerogravity assist and the TPS readiness. This talk will highlight both aerocapture and aerogravity assist from a TPS perspective. The main objective of this proposed talk is to present a comprehensive picture of the SOA TPS technology including recent developments. The talk will highlight advances in manufacturing, results from the Decadal White Papers, PMCS and other studies, and aerocapture and aerogravity assist that could play a role in the near or far term in-situ exploration.
The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is the first X-ray slitless imaging spectrograph sounding rocket instrument designed to observe spectrally dispersed soft X-ray images of the solar corona over a wide field-of-view. During the first flight of MaGIXS (MaGIXS-1), occurred on 30 July 2021, several emission lines from coronal structures including X-ray bright points were observed. Further, MaGIXS-1 analysis also demonstrated the successful inversion of overlappograms using robust unfolding algorithms. Given the demonstrated success of MaGIXS-1, the second flight of the instrument with a simplified optical design, MaGIXS-2, is scheduled for 2024 to observe high temperature diagnostic emission lines. Results from MaGIXS-1 discovered dominant missing emission lines near 15A, arising from relatively cool plasma that peaks around 2 MK. This wavelength region hosts several closely spaced satellite lines of Fe XVII, Fe XVI and Fe XV ions, which are expected to be enhanced at lower temperatures and are currently unmodeled in the CHIANTI atomic database. This wavelength region offers one of the most unique diagnostics to measure electron temperature, as well as signatures of equilibrium state of the plasma in active regions, which has not been studied so far. The goal of MaGIXS-3 mission is the to determine coronal heating parameters, such as the spatial and temporal properties of coronal heating events, by measuring discriminating observations, such as electron temperature, effective temperature, density, abundance, and departures from thermal equilibrium of the plasma, by observing the Sun in the SXR wavelength range. To meet this goal, the MaGIXS instrument will be upgraded with a new X-ray telescope mirror that will provide higher spatial and spectral resolution and throughput, allowing for spectral lines to be observed at the relevant spatial and temporal scales. In addition, MaGIXS-3 will also carry The Resolving Inversion Context X-ray Spectrometer (TRICXS), a high dispersion Bragg crystal spectrometer to spectrally resolve the lines near 14.9 to 15.9A, critical to unlock the full diagnostic potential of this wavelength range. Here we will present the preliminary concept design of MaGIXS-3 and discuss the potential observations.
ABSTRACT We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.
This article discusses the paper "Experimental Design for Engineering Dimensional Analysis" by Albrecht et al. (2013, Technometrics). That paper provides and overview of engineering dimensional analysis (DA) for use in developing DA models. The paper proposes methods for generating model-robust experimental designs to supporting fitting DA models. The specific approach is to develop a design that maximizes the efficiency of a specified empirical model (EM) in the original independent variables, subject to a minimum efficiency for a DA model expressed in terms of dimensionless groups (DGs). This discussion article raises several issues and makes recommendations regarding the proposed approach. Also, the concept of spurious correlation is raised and discussed. Spurious correlation results from the response DG being calculated using several independent variables that are also used to calculate predictor DGs in the DA model.
The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) simplifies the evaluation and assessment of robustness factor and cyber resilience that support secure-by-design for advanced reactor nuclear power plants. In this manner, ARCADE supports risk-informed performance based (RIPB) evaluations of cybersecurity through its integration of plant physics with high-fidelity emulations of control systems. This cross domain approach enables comprehensive analysis of control system sensitivities, cyber-attack scenarios, and their consequences. ARCADE has been custom developed to meet the demands identified in Tier 1 of the Tiered Cyber Analysis (TCA) as outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors.
Critical Infrastructure systems(CIs) such as energy, water, transportation and communication are highly interconnected and mutually dependent in complex ways. Robust modeling of CIs interconnections is crucial to identify vulnerabilities in the CIs. We present here a national-scale Infrastructure Vulnerability Analysis System (IVAS) vision leveraging Se- mantic Big Data (SBD) tools, Big Data, and Geographical Information Systems (GIS) tools. We survey existing ap- proaches on vulnerability analysis of critical infrastructures and discuss relevant systems and tools aligned with our vi- sion. Next, we present a generic system architecture and discuss challenges including: (1) Constructing and manag- ing a CI network-of-networks graph, (2) Performing analytic operations at scale, and (3) Interactive visualization of ana- lytic output to generate meaningful insights. We argue that this architecture acts as a baseline to realize a national-scale network based vulnerability analysis system.
This paper describes an integrated, multi-fidelity analysis and heuristic design approach that can be used to derive initial airfoil designs for transonic flight. If successful, the final result is a geometry that can be expected to produce reasonable aerodynamic performance when used with higher order analysis methods. A key aspect of the methodology is the use of a “sonic-plateau” pressure distribution as the target distribution for inverse design. The sonic- plateau distribution is easily parameterized and has the advantage of automatically resulting in a smooth airfoil shape without any discontinuities built into the surface due to the presence of a shock in the target pressure distribution. Inverse design is performed on each airfoil using a parametrically defined pressure distribution at a reduced lift coefficient and Mach number from the design condition. The methodology is demonstrated by designing an airfoil at 38% of the wing semispan for a 737-200-like aircraft. The demonstration problem shows that the methodology is able to achieve rapid and robust convergence to the solution. The calculated designed airfoil was found to be sufficiently higher than Mach number, and the maximum thickness was close to the targeted value.
A robust performance-based cost model is developed for all-vanadium, iron-vanadium and iron chromium redox flow batteries. Systems aspects such as shunt current losses, pumping losses and thermal management are accounted for. The objective function, set to minimize system cost, allows determination of stack design and operating parameters such as current density, flow rate and depth of discharge (DOD). Component costs obtained from vendors are used to calculate system costs for various time frames. A 2 kW stack data was used to estimate unit energy costs and compared with model estimates for the same size electrodes. The tool has been shared with the redox flow battery community to both validate their stack data and guide future direction.
New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by ≥1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.
Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.
The traditional design and analysis practice for advanced propulsion systems relies heavily on expensive full-scale prototype development and testing. Over the past decade, use of high-fidelity analysis and design tools such as CFD early in the product development cycle has been identified as one way to alleviate testing costs and to develop these devices better, faster and cheaper. In the design of advanced propulsion systems, CFD plays a major role in defining the required performance over the entire flight regime, as well as in testing the sensitivity of the design to the different modes of operation. Increased emphasis is being placed on developing and applying CFD models to simulate the flow field environments and performance of advanced propulsion systems. This necessitates the development of next generation computational tools which can be used effectively and reliably in a design environment. The turbomachinery simulation capability presented here is being developed in a computational tool called Loci-STREAM [1]. It integrates proven numerical methods for generalized grids and state-of-the-art physical models in a novel rule-based programming framework called Loci [2] which allows: (a) seamless integration of multidisciplinary physics in a unified manner, and (b) automatic handling of massively parallel computing. The objective is to be able to routinely simulate problems involving complex geometries requiring large unstructured grids and complex multidisciplinary physics. An immediate application of interest is simulation of unsteady flows in rocket turbopumps, particularly in cryogenic liquid rocket engines. The key components of the overall methodology presented in this paper are the following: (a) high fidelity unsteady simulation capability based on Detached Eddy Simulation (DES) in conjunction with second-order temporal discretization, (b) compliance with Geometric Conservation Law (GCL) in order to maintain conservative property on moving meshes for second-order time-stepping scheme, (c) a novel cloud-of-points interpolation method (based on a fast parallel kd-tree search algorithm) for interfaces between turbomachinery components in relative motion which is demonstrated to be highly scalable, and (d) demonstrated accuracy and parallel scalability on large grids (approx 250 million cells) in full turbomachinery geometries.