Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Functional priors”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

Assessment of cockpit interface concepts for data link retrofit

The problem is examined of retrofitting older generation aircraft with data link capability. The approach taken analyzes requirements for the cockpit interface, based on review of prior research and opinions obtained from subject matter experts. With this background, essential functions and constraints for a retrofit installation are defined. After an assessment of the technology available to meet the functions and constraints, candidate design concepts are developed. The most promising design concept is described in detail. Finally, needs for further research and development are identified.

Mccauley, Hugh W.↗

Reducing Centroid Error Through Model-Based Noise Reduction

A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.

Lee, Shinhak↗

An Architecture to Enable Autonomous Control of Spacecraft

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

space power systems↗

Opportunities for Accelerating Research in the Cloud

As the data holdings of the Earth Observation System Data and Information System expand over the next several years, the typical data analysis process of downloading data to local compute resources will become increasingly inefficient. However, cloud computing promises to mitigate that by allowing the user to process close to the data. These improvements will be obtained via a variety of mechanisms: 1 - improving the ability of data transformation services to reduce the data prior to analysis; 2 - providing cloud-native analysis capabilities for common analysis functions; and 3 - providing the ability to work directly with data in Web Object Storage.

data system↗

Development Efforts and Status of Plume-Surface Interaction Capabilities for Propulsive Landing Systems

Rocket plume-surface interaction is a multi-phase problem characterized by plume flow physics, erosion physics, and ejecta dynamics. All propulsive landers will experience plume-surface interaction. The risks posed by such effects can vary greatly as a function of the local environment, lander concept of operations, configuration, and physical scale. Prior Lunar and Martian landers have overcome challenges posed by these environments, on the basis of scaled ground testing and subsequent flight experience, but the landing systems for present and future missions are planning to operate increasingly outside of NASA's current experience with plume-surface interaction. This presentation discusses the current efforts and status of activities within NASA to progress understanding of fundamental plume-surface interaction physics, the capability to predict resulting environments and effects, and the definition of implications for current and future Lunar and planetary landing systems.

Landing↗

Green Run Modal Test of the NASA Space Launch System Core Stage

The Core Stage of the new NASA Space Launch System (SLS) is a 212-foot-tall rocket assembly—consisting primarily of two cryogenic propellant tanks, an engine section, and four RS-25 rocket engines—that will send crew and large payloads to the moon and beyond for NASA’s Artemis program. Prior to SLS assembly, the Core Stage completed a series of structural and functional tests in the B-2 Test Stand at Stennis Space Center, designated Green Run. The goal of Green Run was to verify analytical models, confirm proper subsystem operation, and test-fire all four RS-25 engines of the Core Stage. In January 2020, Green Run testing began with an experimental modal analysis test, performed by the Marshal Space Flight Center modal test team. A free-boundary test condition of the Core Stage was simulated as close as possible by suspending the massive launch vehicle from the B-2 Test Stand crane. Modal excitation was provided by a pair of 250-lb electro-dynamic shakers for multi-shaker random vibration testing, as well as a 12-pound instrumented hammer for impact testing. Modal response was measured with 550 accelerometer channels distributed on both the Core Stage and the B-2 Test Stand derrick crane. Following one very long day of testing, frequency response functions were calculated from the measured time histories in the target mode frequency range of 5 Hz to 15 Hz, and mode shapes, frequencies, and damping values were successfully estimated. The case-study presented in this paper will discuss Green Run, the SLS Core Stage, the modal test setup and execution, as well as a brief overview of the test results. Challenges associated with testing such a large, suspended structure in an outdoor environment will be discussed as well.

Space Launch System↗

Improved CLARAty Functional-Layer/Decision-Layer Interface

Improved interface software for communication between the CLARAty Decision and Functional layers has been developed. [The Coupled Layer Architecture for Robotics Autonomy (CLARAty) was described in Coupled-Layer Robotics Architecture for Autonomy (NPO-21218), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48. To recapitulate: the CLARAty architecture was developed to improve the modularity of robotic software while tightening coupling between planning/execution and basic control subsystems. Whereas prior robotic software architectures typically contained three layers, the CLARAty contains two layers: a decision layer (DL) and a functional layer (FL).] Types of communication supported by the present software include sending commands from DL modules to FL modules and sending data updates from FL modules to DL modules. The present software supplants prior interface software that had little error-checking capability, supported data parameters in string form only, supported commanding at only one level of the FL, and supported only limited updates of the state of the robot. The present software offers strong error checking, and supports complex data structures and commanding at multiple levels of the FL, and relative to the prior software, offers a much wider spectrum of state-update capabilities.

Estlin, Tara↗

Motor power factor controller with a reduced voltage starter

A power factor type motor controller in which the conventional power factor constant voltage command signal is replaced during a starting interval with a graduated control voltage. The present invention adds to the three-phase system of pending application Ser. No. 199,765, filed Oct. 23, 1980, means for modifying the operation of the system for a motor start-up interval of 5 to 30 seconds. The modification is that of providing via ramp generator 174 an initial ramp-like signal which replaces a constant power factor signal supplied by potentiometer 70. The ramp-like signal is applied to terminal 40 where it is summed with an operating power factor signal from phase detectors 32, 34, and 36 to thereby obtain a control signal for ultimately controlling SCR devices 12, 14, and 16 to effect a gradual turn-on of motor 10. The significant difference of the present invention over prior art is that the SCR devices are turned on at an advancing rate with time responsive to the combination signal described rather than simply a function of a ramp-like signal alone. The added signal, the operating power factor signal, enables the production of a control signal which effectively eliminates a prior problem with many motor starting circuits, which is that of accompanying motor instabilities.

Nola, Frank J.↗

Functional roles of the [2Fe-2S] clusters in Synechocystis PCC 6803 Hox [NiFe]-hydrogenase reactivity with ferredoxins

The HoxEFUYH complex of Synechocystis PCC 6803 (S. 6803) consists of a HoxEFU ferredoxin:NAD(P)H oxidoreductase subcomplex and a HoxYH [NiFe]-hydrogenase subcomplex that catalyzes reversible H2 oxidation. Prior studies have suggested that the presence of HoxE is required for reactivity with ferredoxin; however, it is unknown how HoxE is functionally integrated into the electron transfer network of the HoxEFU:ferredoxin complex. Deciphering electron transfer pathways is challenged by the rich iron-sulfur cluster content of HoxEFU, which includes a [2Fe-2S] cluster in each subunit, along with multiple [4Fe-4S] clusters and a flavin cofactor. To resolve the role of HoxE, we determined the biophysical and thermodynamic properties of each [2Fe-2S] cluster in HoxEFU using steady-state and potentiometric EPR analysis in combination with square wave voltammetry (SWV). The temperature-dependence of the EPR signal for HoxE confirmed the coordination of a single [2Fe-2S] cluster that was shown by SWV to have an E m = -424 mV (versus SHE). Strikingly, when the E m of the HoxE [2Fe-2S] cluster was analyzed in HoxEFU titrations, it was shifted by >100 mV to an E m < -525 mV (versus SHE). EPR titrations of HoxEFU gave an E m value for the [2Fe-2S] cluster of HoxF, E m = -419 mV and HoxU, E m = -349 mV. These values were used to re-analyze the diaphorase kinetics in reactions performed with ferredoxins with varying E m 's. The results are formulated into a model of HoxEFU:ferredoxin reactivity and the role of HoxE in mediating electron transfer within the HoxEFU:ferredoxin complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diet as a factor in behavioral radiation protection following exposure to heavy particles

Major risks associated with radiation exposures on deep space missions include carcinogenesis due to heavy-particle exposure of cancer-prone tissues and performance decrements due to neurological damage produced by heavy particles. Because exposure to heavy particles can cause oxidative stress, it is possible that antioxidants can be used to mitigate these risks (and possibly some health risks of microgravity). To assess the capacity of antioxidant diets to mitigate the effects of exposure to heavy particles, rats were maintained on antioxidant diets containing 2% blueberry or strawberry extract or a control diet for 8 weeks prior to exposure to 1.5 or 2.0 Gy of accelerated iron particles at Brookhaven National Laboratory. Following irradiation rats were tested on a series of behavioral tasks: amphetamine-induced taste aversion learning, operant responding and spatial learning and memory. The results indicated that the performance of the irradiated rats maintained on the antioxidant diets was, in general, significantly better than that of the control animals, although the effectiveness of the diets ameliorating the radiation-induced deterioration in performance varied as a function of both the specific diet and the specific endpoint. In addition, animals fed antioxidant diets prior to exposure showed reduced heavy particle-induced tumorigenesis one year after exposure compared to the animals fed the control diet. These results suggest that antioxidant diets have the potential to serve as part of a system designed to provide protection to astronauts against the effects of heavy particles on exploratory missions outside the magnetic field of the earth.

Non-NASA Center↗

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗

Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process

Abstract Both experimental and computational methods for the exploration of structure, functionality, and properties of materials often necessitate the search across broad parameter spaces to discover optimal experimental conditions and regions of interest in the image space or parameter space of computational models. The direct grid search of the parameter space tends to be extremely time-consuming, leading to the development of strategies balancing exploration of unknown parameter spaces and exploitation towards required performance metrics. However, classical Bayesian optimization (BO) strategies based on the Gaussian process (GP) do not readily allow for the incorporation of the known physical behaviors or past knowledge. Here we explore a hybrid optimization/exploration algorithm created by augmenting the standard GP with a structured probabilistic model of the expected system’s behavior. This approach balances the flexibility of the non-parametric GP approach with a rigid structure of physical knowledge encoded into the parametric model. The fully Bayesian treatment of the latter allows additional control over the optimization via the selection of priors for the model parameters. The method is demonstrated for a noisy version of a standard univariate test function used to evaluate optimization algorithms and further extended to physical lattice models. This methodology is expected to be universally suitable for injecting prior knowledge in the form of physical models and past data in the BO framework.

42 ENGINEERING↗

Response Versus Scan-Angle Corrections for MODIS Reflective Solar Bands Using Deep Convective Clouds

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the performance of the SD over time, provides the absolute reference for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the zero input radiance, respectively. The MODIS instrument views the Earth's surface through a two-sided scan mirror, whose reflectance is a function of angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different assigned RVS positions. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent in the left side Earth-view scans.

Bhatt, Rajendra↗

Response Versus Scan-Angle Corrections for MODIS Reflective Solar Bands Using Deep Convective Clouds

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the performance of the SD over time, provides the absolute reference for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the zero input radiance, respectively. The MODIS instrument views the Earths surface through a two-sided scan mirror, whose reflectance is a function of angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different assigned RVS positions. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent in the left side Earth-view scans.

Bhatt, Rajendra↗

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity

The transition between gravity environments will involve one of the most complex, high-risk phases of any mission. For example, the reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk scenarios may be required to be performed soon after gravity transitions: • Nominal and/or emergency unassisted capsule egress task after return to Earth • Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study is broken down into two phases. Phase 1: A feasibility study that will assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing. Phase 2: the full Egress Fitness study, which is part of the CIPHER complement. This study uses a task-based approach to characterize functional performance of these high-risk scenarios in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and a mobility assessment to confirm completion of the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth-based emergency egress out of a functional capsule mockup and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing will occur at any time point prior to flight. Post-flight assessment is much more critical with the capsule egress test that will occur 1–4 hours after landing and the planetary EVA approximately 18–36 hours after landing. The CIPHER study will incorporate additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. Data collected for both tasks include task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed both baseline and post-flight testing on four astronaut subjects, with all four able to complete post-flight EVA testing and three able to complete postflight capsule egress testing. Preliminary results observe individual physiological variations, which were to be expected but also suggest the need to carefully track the timeline from undock to landing to testing. Furthermore, some task performance instructions and equipment may need to be adjusted to ensure results are primarily physiological. These and other lessons learned will be addressed with minor protocol changes in the full CIPHER Egress Fitness study.

J R Norcross↗

Qualitative trend analysis based on a mixed-integer representation

Shape constrained spline fitting is a useful method to impose prior knowledge onto flexible semi-parametric models during parameter estimation. Most typically, the function shape is imposed through order restrictions on the regression coefficients. The intended shape is considered known or selected based on heuristic rules. In this study, we present a method to estimate the optimal set of order restrictions to segment a univariate data series into episodes with distinct shapes. This is also known as the qualitative trend analysis (QTA) problem. The obtained solution uses a trade-off between lack-of-fit and model complexity. Further, our practical implementation takes inspiration from the generalized order restricted information criterion (GORIC) for inequality-constrained model selection. From this, one learns (a) that QTA can be formulated as a mixed-integer quadratic program (MIQP) and (b) that the newly proposed mixed order restricted information criterion (MORIC) enables optimal segmentation. This is illustrated through didactic case studies.

42 ENGINEERING↗

Nonlinear sparse Bayesian learning for physics-based models

This paper addresses the issue of overfitting while calibrating unknown parameters of over-parameterized physics-based models with noisy and incomplete observations. Here, a semi-analytical Bayesian framework of nonlinear sparse Bayesian learning (NSBL) is proposed to identify sparsity among model parameters during Bayesian inversion. NSBL offers significant advantages over machine learning algorithm of sparse Bayesian learning (SBL) for physics-based models, such as 1) the likelihood function or the posterior parameter distribution is not required to be Gaussian, and 2) prior parameter knowledge is incorporated into sparse learning (i.e. not all parameters are treated as questionable). NSBL employs the concept of automatic relevance determination (ARD) to facilitate sparsity among questionable parameters through parameterized prior distributions. The analytical tractability of NSBL is enabled by employing Gaussian ARD priors and by building a Gaussian mixture-model approximation of the posterior parameter distribution that excludes the contribution of ARD priors. Subsequently, type-II maximum likelihood is executed using Newton's method whereby the evidence and its gradient and Hessian information are computed in a semi-analytical fashion. We show numerically and analytically that SBL is a special case of NSBL for linear regression models. Subsequently, a linear regression example involving multimodality in both parameter posterior pdf and model evidence is considered to demonstrate the performance of NSBL in cases where SBL is inapplicable. Next, NSBL is applied to identify sparsity among the damping coefficients of a mass-spring-damper model of a shear building frame. These numerical studies demonstrate the robustness and efficiency of NSBL in alleviating overfitting during Bayesian inversion of nonlinear physics-based models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Causal discovery from data assisted by large language models

Knowledge-driven discovery of novel materials necessitates the development of causal models for property emergence. While in the classical physical paradigm, the causal relationships are deduced based on physical principles or via experiment, the rapid accumulation of observational data necessitates learning causal relationships between dissimilar aspects of material structure and functionalities based on observations. For this, it is essential to integrate experimental data with prior domain knowledge. Here, we demonstrate this approach by combining high-resolution scanning transmission electron microscopy data with insights derived from large language models (LLMs). By applying ChatGPT to domain-specific literature, such as arXiv papers on ferroelectrics, and combining the obtained information with data-driven causal discovery, we construct adjacency matrices for directed acyclic graphs that map the causal relationships between structural, chemical, and polarization degrees of freedom in Sm-doped BiFeO 3 . This approach enables us to hypothesize how synthesis conditions influence material properties and guides experimental validation. Furthermore, the ultimate objective of this work is to develop a unified framework that integrates LLM-driven literature analysis with data-driven discovery, facilitating the precise engineering of ferroelectric materials by establishing clear connections between synthesis conditions and their resulting material properties.

Causal inference↗