Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Scientific method”

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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

MSL Chemistry and Mineralogy X-Ray Diffraction X-Ray Fluorescence (CheMin) Instrument

This paper provides an overview of the Mars Science Laboratory (MSL) Chemistry and Mineralogy Xray Diffraction (XRD), X-ray Fluorescence (XRF) (CheMin) Instrument, an element of the landed Curiosity rover payload, which landed on Mars in August of 2012. The scientific goal of the MSL mission is to explore and quantitatively assess regions in Gale Crater as a potential habitat for life - past or present. The CheMin instrument will receive Martian rock and soil samples from the MSL Sample Acquisition/Sample Processing and Handling (SA/SPaH) system, and process it utilizing X-Ray spectroscopy methods to determine mineral composition. The Chemin instrument will analyze Martian soil and rocks to enable scientists to investigate geophysical processes occurring on Mars. The CheMin science objectives and proposed surface operations are described along with the CheMin hardware with an emphasis on the system engineering challenges associated with developing such a complex instrument.

sample chemistry↗
NASA NTRS2022

ISS Payload Operations Training Throughout the COVID-19 Pandemic: Impacts, Opportunities and Solutions

The onset of the COVID-19 pandemic brought a dramatic and rapid transformation to almost every aspect of humanity. The world’s space agencies and their missions were not immune to the wide-sweeping changes. One discipline principally affected was mission operations and the various groups supporting that function. Mission support teams, especially for complex and crewed missions like the International Space Station (ISS) were forced to rethink how and where control center staff performed their vital work. Operations training – an essential element to mission ops, had unique hurdles to overcome. Operations training is responsible for preparing astronaut crews for their missions, training and certifying flight controllers, as well as ensuring that new team members are ready to join their colleagues. Every element of training was impacted during the pandemic. From orientation and introductory classes for new controllers, simulations, and advanced lessons, On the Job Training (OJT) and final evaluations; all aspects faced challenges. Trainers at NASA’s Marshall Space Flight Center in Huntsville, Alabama were forced to become more efficient with trainees and resources to continue supporting ISS payload operations. The pandemic arrived in the USA in March 2020. Immediately, NASA mandated that the support for ISS real-time operations was critical. As a result, physical access to key facilities was restricted. Trainers and trainees had to quickly shift to 100% remote learning. In the short term, this was not a problem. However, instructors discovered lessons they were accustomed to delivering in a classroom environment often did not translate to remote teaching. Another hurdle to operations training was the mandate that all simulations could only be held remotely. The logistics of even small simulations proved to be challenging due to Information Technology (IT) restrictions and public internet limitations. With simulations essentially halted, as well as the restrictions on most OJT, trainees were essentially stopped in their advancement towards certification. Once limitations were identified, trainers prioritized new options. Transitioning to all electronic learning materials was a relatively easy fix. Teaching to large groups took additional shifts in the training paradigm. Methods for preparing astronauts for their missions were revised. Simulation supervisors found efficient techniques to provide realistic training experiences. Communication and coordination with management was essential. In every case, the payload operations instructors found novel solutions to all functions listed. This paper discusses the factors and solutions payloads operations trainers found to keep scientific research on the ISS flying forward to mission success.

ISS↗
NASA NTRSDate not supplied

Performance Analysis of Magnetohydrodynamic Drag Modulation for Actively Controlled Aerocapture at Neptune

Missions to the Ice Giants are a top priority for flagship missions this coming decade. However, a fully propulsive orbital insertion into these planets requires an immense amount of fuel, taking a significant portion of the spacecraft mass and restricting the scientific payload. To mitigate this, aerocapture has been heavily investigated. Although simulations have shown that aerodynamically controlled aerocapture can successfully insert into an orbit around both Ice Giants, the deep atmospheric pass required necessitates a complex, mass expensive, and sometimes prohibitive thermal protection system. Magnetohydrodynamic drag modulation serves as a potential alternative control method for aerocapture which could not only save propellant mass compared to fully propulsive orbital insertion, but also save thermal protection system mass compared to conventional aerocapture methods. Both aerodynamically controlled and magnetohydrodynamically controlled aerocapture methodologies were simulated in NASA Langley’s high-fidelity six degree-of-freedom flight dynamics code, the Program to Optimize Simulated Trajectories II. Each method was simulated to identical missions to Neptune using a numerical predictor-corrector algorithm to optimize the control towards the target orbit. The results concluded that magnetohydrodynamic drag modulation can successfully capture and performs on par with aerodynamic drag modulation while significantly reducing the heatflux and aeroshell complexity.

Danny N Nguyen↗
NASA NTRS2001

Non-Deterministic, Non-Traditional Methods (NDNTM)

The review effort identified research opportunities related to the use of nondeterministic, nontraditional methods to support aerospace design. The scope of the study was restricted to structural design rather than other areas such as control system design. Thus, the observations and conclusions are limited by that scope. The review identified a number of key results. The results include the potential for NASA/AF collaboration in the area of a design environment for advanced space access vehicles. The following key points set the context and delineate the key results. The Principal Investigator's (PI's) context for this study derived from participation as a Panel Member in the Air Force Scientific Advisory Board (AF/SAB) Summer Study Panel on 'Whither Hypersonics?' A key message from the Summer Study effort was a perceived need for a national program for a space access vehicle whose operating characteristics of cost, availability, deployability, and reliability most closely match the NASA 3rd Generation Reusable Launch Vehicle (RLV). The Panel urged the AF to make a significant joint commitment to such a program just as soon as the AF defined specific requirements for space access consistent with the AF Aerospace Vision 2020. The review brought home a concurrent need for a national vehicle design environment. Engineering design system technology is at a time point from which a revolution as significant as that brought about by the finite element method is possible, this one focusing on information integration on a scale that far surpasses current design environments. The study therefore fully supported the concept, if not some of the details of the Intelligent Synthesis Environment (ISE). It became abundantly clear during this study that the government (AF, NASA) and industry are not moving in the same direction in this regard, in fact each is moving in its own direction. NASA/ISE is not yet in an effective leadership position in this regard. However, NASA does have complementary software interoperability efforts that should be a part of any major ISE program. Software standards that assure interoperability of data systems and modeling representations are enabling for the proposed research advocated herein and should be a major element in the ISE initiative. The international standard for data interchange is known by the acronym 'STEP.' The NASA participation and lead for that effort is at the Goddard Space Flight Center. NASA/GRC is leading an effort to define CAD geometry standards through the Object Management Group (OMG). To enable the design environment so necessary to the above national vision for a unique space vehicle will require an integrating software environment with interoperability standards that allow the development and widespread deployment of tools and toolsets, rather than traditional "shrink-wrapped" software used by engineers today.

Cruse, Thomas A.↗
DOE OSTI2020

Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

Here in this work we present a non-intrusive model reduction method to learn low-dimensional models of dynamical systems with non-polynomial nonlinear terms that are spatially local and that are given in analytic form. In contrast to state-of-the-art model reduction methods that are intrusive and thus require full knowledge of the governing equations and the operators of a full model of the discretized dynamical system, the proposed approach requires only the non-polynomial terms in analytic form and learns the rest of the dynamics from snapshots computed with a potentially black-box full-model solver. The proposed method learns operators for the linear and polynomially nonlinear dynamics via a least-squares problem, where the given non-polynomial terms are incorporated on the right-hand side. The least-squares problem is linear and thus can be solved efficiently in practice. The proposed method is demonstrated on three problems governed by partial differential equations, namely the diffusion–reaction Chafee–Infante model, a tubular reactor model for reactive flows, and a batch-chromatography model that describes a chemical separation process. The numerical results provide evidence that the proposed approach learns reduced models that achieve comparable accuracy as models constructed with state-of-the-art intrusive model reduction methods that require full knowledge of the governing equations.

42 ENGINEERING↗
DOE OSTI2025

Autonomous alloy composition optimization using molecular dynamics guided by a large language model

Here, we present an autonomous materials discovery framework that couples a large language model (LLM) with molecular dynamics (MD) simulations to optimize Fe–Cr–Mn alloy compositions for tensile strength. Starting from six distinct compositions, the LLM operated as an intelligent agent, iteratively proposing changes based on prior simulation results and constraints. Over 50 iterations per case, the LLM adaptively explored the composition space, identifying high-strength regions, not easily accessible by conventional methods. The highest strength, 18.7 GPa, was achieved with Fe 71 Cr 25 Mn 4 composition, identified from a Fe 75 Cr 20 Mn 5 starting point. The LLM autonomously adjusted its strategy in real time, demonstrating closed-loop decision-making using commodity hardware. This approach showcases the potential of LLMs as scientific co-pilots, capable of accelerating materials discovery and generalizable to other domains like biology and drug design.

Autonomy↗
DOE OSTI2022

Robust estimation of charge carrier diffusivity using transient photoluminescence microscopy

Transient microscopy has emerged as a powerful tool for imaging the diffusion of excitons and free charge carriers in optoelectronic materials. In many excitonic materials, extraction of diffusion coefficients can be simplified because of the linear relationship between signal intensity and local excited state population. However, in materials where transport is dominated by free charge carriers, extracting diffusivities accurately from multidimensional data is complicated by the nonlinear dependence of the measured signal on the local charge carrier density. To obtain accurate estimates of charge carrier diffusivity from transient microscopy data, statistically robust fitting algorithms coupled to efficient 3D numerical solvers that faithfully relate local carrier dynamics to raw experimental measurables are sometimes needed. Here, we provide a detailed numerical framework for modeling the spatiotemporal dynamics of free charge carriers in bulk semiconductors with significant solving speed reduction and for simulating the corresponding transient photoluminescence microscopy data. To demonstrate the utility of this approach, we apply a fitting algorithm using a Markov chain Monte Carlo sampler to experimental data on bulk CdS and methylammonium lead bromide (MAPbBr 3 ) crystals. Parameter analyses reveal that transient photoluminescence microscopy can be used to obtain robust estimates of charge carrier diffusivities in optoelectronic materials of interest, but that other experimental approaches should be used for obtaining carrier recombination constants. Additionally, simplifications can be made to the fitting model depending on the experimental conditions and material systems studied. Our open-source simulation code and fitting algorithm are made freely available to the scientific community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

On Transfer Learning Of Neural Networks Using Bi-Fidelity Data For Uncertainty Propagation

Due to their high degree of expressiveness, neural networks have recently been used as surrogate models for mapping inputs of an engineering system to outputs of interest. Once trained, neural networks are computationally inexpensive to evaluate and remove the need for repeated evaluations of computationally expensive models in uncertainty quantification applications. However, given the highly parameterized construction of neural networks, especially deep neural networks, accurate training often requires large amounts of simulation data that may not be available in the case of computationally expensive systems. In this paper, to alleviate this issue for uncertainty propagation, we explore the application of transfer learning techniques using training data generated from both high- and low-fidelity models. We explore two strategies for coupling these two datasets during the training procedure, namely, the standard transfer learning and the bi-fidelity-weighted learning. In the former approach, a neural network model mapping the inputs to the outputs of interest is trained based on the low-fidelity data. The high-fidelity data are then used to adapt the parameters of the upper layer(s) of the low-fidelity network, or train a simpler neural network to map the output of the low-fidelity network to that of the high-fidelity model. In the latter approach, the entire low-fidelity network parameters are updated using data generated via a Gaussian process model trained with a small high-fidelity dataset. The parameter updates are performed via a variant of stochastic gradient descent with learning rates given by the Gaussian process model. Using three numerical examples, we illustrate the utility of these bi-fidelity transfer learning methods where we focus on accuracy improvement achieved by transfer learning over standard training approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Lost in transduction: Critical considerations when using viral vectors

The application of retroviral vectors in the laboratory requires considerations that often go overlooked but are often easy to circumvent. Here, we discuss the relationship between the observed transduction efficiency of a cell population and per-cell viral insertions—and describe how differential cell-type susceptibilities can confound results. We consider the math underlying this problem and review an alternative approach to the commonly used “multiplicity of infection” (MOI) method of titering and using viral vectors in the biomedical research laboratory.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

The Valuation of Scientific and Technical Experiments

Rational selection of scientific and technical experiments for space missions is studied. Particular emphasis is placed on the assessment of value or worth of an experiment. A specification procedure is outlined and discussed for the case of one decision maker. Experiments are viewed as multi-attributed entities, and a relevant set of attributes is proposed. Alternative methods of describing levels of the attributes are proposed and discussed. The reasonableness of certain simplifying assumptions such as preferential and utility independence is explored, and it is tentatively concluded that preferential independence applies and utility independence appears to be appropriate.

Williams, F. E.↗
NASA NTRS1988

Mars sample return - Science

The possible scientific goals of a Mars sample return mission are reviewed, including the value of samples and the selection of sampling sites. The fundamental questions about Mars which could be studied using samples are examined, including planetary formation, differentiation, volcanism and petrogenesis, weathering, and erosion. Scenarios are presented for sample acquisition and analysis. Possible sampling methods and tools are discussed, including drilling techniques, types of rovers, and processing instruments. In addition, the possibility of aerocapture out of elliptical or circular orbit is considered.

Blanchard, Douglas P.↗
NASA NTRS1990

Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

Strub, P. Ted↗
NASA NTRS1993

Comparison of TOPEX/Poseidon orbit determination solutions obtained by the Goddard Space Flight Center Flight Dynamics Division and Precision Orbit Determination Teams

Orbit determination results are obtained by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) using the Goddard Trajectory Determination System (GTDS) and a real-time extended Kalman filter estimation system to process Tracking Data and Relay Satellite (TDRS) System (TDRSS) measurements in support of the Ocean Topography Experiment (TOPEX)/Poseidon spacecraft navigation and health and safety operations. GTDS is the operational orbit determination system used by the FDD, and the extended Kalman fliter was implemented in an analysis prototype system, the Real-Time Orbit Determination System/Enhanced (RTOD/E). The Precision Orbit Determination (POD) team within the GSFC Space Geodesy Branch generates an independent set of high-accuracy trajectories to support the TOPEX/Poseidon scientific data. These latter solutions use the Geodynamics (GEODYN) orbit determination system with laser ranging tracking data. The TOPEX/Poseidon trajectories were estimated for the October 22 - November 1, 1992, timeframe, for which the latest preliminary POD results were available. Independent assessments were made of the consistencies of solutions produced by the batch and sequential methods. The batch cases were assessed using overlap comparisons, while the sequential cases were assessed with covariances and the first measurement residuals. The batch least-squares and forward-filtered RTOD/E orbit solutions were compared with the definitive POD orbit solutions. The solution differences were generally less than 10 meters (m) for the batch least squares and less than 18 m for the sequential estimation solutions. The differences among the POD, GTDS, and RTOD/E solutions can be traced to differences in modeling and tracking data types, which are being analyzed in detail.

Doll, C.↗
NASA NTRS2003

Optimization Of Ocean Color Algorithms: Application To Satellite And In Situ Data Merging

The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project (McClain et al., 1995). The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage (Gregg et al., 1998; Gregg & Woodward, 1998). The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global ocean the merging of ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program (see e.g. Kwiatkowska & Fargion, 2003, Franz et al., 2003). As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized waterleaving radiances (LwN( )) from single or multiple sensors and uses them in the inversion of a semianalytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the LwN( ) data and, 4) it provides uncertainty estimates for the retrieved variables.

Maritorena, Stephane↗
NASA NTRS2008

Hyperspectral Sun Photometer for Atmospheric Characterization and Vicarious Calibrations

A hyperspectral sun photometer and associated methods have been developed and demonstrated. Accurate sun photometer calibration is critical to properly measure the solar irradiance and characterize the atmosphere. Traditional sun photometer calibration requires solar observations over several hours. In contrast, the procedures for operating this photometer entail less data acquisition time and embody a more direct approach to calibration. The scientific value of the measurement data produced by this instrument is not adversely affected by atmospheric instability. In addition, this instrument yields hyperspectral data covering a large spectral range (350-2,500 nm) not available from most traditional sun photometers. The hyperspectral sun photometer components include (1) a commercially available spectroradiometer that has been laboratory-calibrated and (2) a commercially available reflectance standard panel that exhibits nearly Lambertian 99% reflectance. The spectroradiometer is positioned above, and aimed downward at, the panel. The procedure for operating this instrument calls for a series of measurements: one in which the panel is fully illuminated by the sun, one in which a shade is positioned between the panel and the sun, and two in which the shade is positioned to cast a shadow to either side of the panel. The total sequence of measurements can be performed in less than a minute. From these measurements, the total radiance, the diffuse radiance, and the direct solar radiance are calculated. The direct solar irradiance is calculated from the direct solar radiance and the known reflectance factor of the panel as a function of the solar zenith angle. Atmospheric characteristics are estimated from the optical depth at various wavelengths calculated from (1) the direct solar irradiance obtained as described above, (2) the air mass along a column from the measurement position to the Sun, and (3) the top-of-atmosphere solar irradiance. The instrumentation used to implement the sun photometer is the same as that used to characterize targets used in radiometric vicarious calibrations. Utilizing this type of sun photometer thus reduces the amount of instrumentation and labor required to perform these studies.

Pagnutti, Mary↗
NASA NTRS2013

SIM_EXPLORE: Software for Directed Exploration of Complex Systems

Physics-based numerical simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. While such codes may provide the highest- fidelity representation of system behavior, they are often so slow to run that insight into the system is limited. Trying to understand the effects of inputs on outputs by conducting an exhaustive grid-based sweep over the input parameter space is simply too time-consuming. An alternative approach called "directed exploration" has been developed to harvest information from numerical simulators more efficiently. The basic idea is to employ active learning and supervised machine learning to choose cleverly at each step which simulation trials to run next based on the results of previous trials. SIM_EXPLORE is a new computer program that uses directed exploration to explore efficiently complex systems represented by numerical simulations. The software sequentially identifies and runs simulation trials that it believes will be most informative given the results of previous trials. The results of new trials are incorporated into the software's model of the system behavior. The updated model is then used to pick the next round of new trials. This process, implemented as a closed-loop system wrapped around existing simulation code, provides a means to improve the speed and efficiency with which a set of simulations can yield scientifically useful results. The software focuses on the case in which the feedback from the simulation trials is binary-valued, i.e., the learner is only informed of the success or failure of the simulation trial to produce a desired output. The software offers a number of choices for the supervised learning algorithm (the method used to model the system behavior given the results so far) and a number of choices for the active learning strategy (the method used to choose which new simulation trials to run given the current behavior model). The software also makes use of the LEGION distributed computing framework to leverage the power of a set of compute nodes. The approach has been demonstrated on a planetary science application in which numerical simulations are used to study the formation of asteroid families.

Burl, Michael↗
NASA NTRSDate not supplied

Deep Convective Cloud Calibration Sensitivity Studies in Support of Radiometrically Scaling GEO Imagers With VIIRS

The NASA CERES SYN1deg product provides the scientific community regional hourly TOA and surface broadband fluxes and clouds. For consistent geostationary (GEO) derived fluxes and clouds the GEO imagers are radiometrically scaled to the Aqua-MODIS calibration reference. The CERES project utilizes GEO and MODIS or VIIRS analogous channel coincident, collocated, and co-angled radiance pairs as the primary method to inter-calibrate the GEO imagers. Tropical deep convective clouds (DCC) are bright, near Lambertian, top of atmosphere pseudo invariant Earth targets that do not rely on coincident ray-matched radiance pairs to radiometrically scale sensors to a common calibration reference. The DCC invariant target (DCC-IT) methodology collectively analyzes all tropical DCC identified pixel radiances by way of probability density function (PDF) distributions. Perfectly inter-calibrated sensor pairs should reveal nearly identical PDF distributions given the same DCC identification criterion. The PDF median, mean, mode, and inflection point statistics were tested as a function of DCC identification criterion using SNPP-VIIRS and Himawari-8 AHI 0.65μm channel radiances during January 2019. It was found that the PDF inflection point provided inter-calibration factors within 0.25% that were nearly independent of DCC identification criterion. The PDF median provided inter-calibration factors within 0.25% for the coldest BT and most stringent homogeneity factors. The PDF mean and mode statistics were inadequate under any DCC conditions. It is critical for the DCC pixel radiances to be anisotropically corrected. The DCC-IT methodology will also be tested for other visible and SWIR bands.

DCC↗
DOE OSTI2021

Computational Math Problems for a Clean Energy Future

Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.

ADMM↗