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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Early differential cell death and survival mechanisms initiate and contribute to the development of OPIDN: A study of molecular, cellular, and anatomical parameters

Organophosphorus-ester induced delayed neurotoxicity (OPIDN) is a neurodegenerative disorder characterized by ataxia progressing to paralysis with a concomitant central and peripheral, distal axonapathy. Diisopropylphosphorofluoridate (DFP) produces OPIDN in the chicken that results in mild ataxia in 7-14 days and severe paralysis as the disease progresses with a single dose. White leghorn layer hens were treated with DFP (1.7 mg/kg, sc) after prophylactic treatment with atropine (1 mg/kg, sc) in normal saline and eserine (1 mg/kg, sc) in dimethyl sulfoxide. Control groups were treated with vehicle propylene glycol (0.1 ml/kg, sc), atropine in normal saline and eserine in dimethyl sulfoxide. The hens were euthanized at different time points such as 1, 2, 5, 10 and 20 days, and the tissues from cerebrum, midbrain, cerebellum, brainstem and spinal cord were quickly dissected and frozen for mRNA (northern) studies. Northern blots were probed with BCL2, GADD45, beta actin, and 28S RNA to investigate their expression pattern. Another set of hens was treated for a series of time points and perfused with phosphate buffered saline and fixative for histological studies. Various staining protocols such as Hematoxylin and Eosin (H and E); Sevier-Munger; Cresyl echt Violet for Nissl substance; and Gallocynin stain for Nissl granules were used to assess various patterns of cell death and degenerative changes. Complex cell death mechanisms may be involved in the neuronal and axonal degeneration. These data indicate altered and differential mRNA expressions of BCL2 (anti apoptotic gene) and GADD45 (DNA damage inducible gene) in various tissues. Increased cell death and other degenerative changes noted in the susceptible regions (spinal cord and cerebellum) than the resistant region (cerebrum), may indicate complex molecular pathways via altered BCL2 and GADD45 gene expression, causing the homeostatic imbalance between cell survival and cell death mechanisms. Semi quantitative analysis revealed that the order of severity of damage declines from the spino-cerebellar, ventral, and dorsal tract respectively, suggesting neuroanatomical specificity. Thus, early activation of cell death and cell survival processes may play significant role in the clinical progression and syndromic clinical feature presentation of OPIDN. -- Highlights: Black-Right-Pointing-Pointer Multiple mechanisms of neurodegeneration were indicated in a study on OPIDN model. Black-Right-Pointing-Pointer Altered expressions of BCL2 and GADD45 were recorded in various tissues of CNS. Black-Right-Pointing-Pointer Multiple anomalous cellular (neuronal and astroglial) features were recorded. Black-Right-Pointing-Pointer Anatomical specificity of the neurodegeneration was described.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A Bayesian approach for parameter estimation and prediction using a computationally intensive model

Bayesian methods have been successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model eta(theta), where theta denotes the uncertain, best input setting. Hence the statistical model is of the form y = eta(theta) + c, where epsilon accounts for measurement, and possibly other, error sources. When nonlinearity is present in eta(center dot), the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and nonstandard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. Although generally applicable, MCMC requires thousands (or even millions) of evaluations of the physics model eta(center dot). This requirement is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory.

Higdon, Dave↗
NASA NTRS1993

Space transportation vehicle design evaluation using saturated designs

An important objective in the preliminary design and evaluation of space transportation vehicles is to find the best values of design variables that optimize the performance characteristic (e.g. dry weight). For a given configuration, the vehicle performance can be determined by the use of complex sizing and performance evaluation computer programs. These complex computer programs utilize iterative algorithms and they are generally too expensive and/or difficult to use directly in multidisciplinary design optimization. An alternative is to use response surface methodology (RSM) and obtain quadratic polynomial approximations to the functional relationships between performance characteristics and design variables. In RSM, these approximation models are then used to determine optimum design parameter values and for rapid sensitivity studies. Constructing a second-order model requires that 'n' design parameters be studied at least at 3 levels (values) so that the coefficients in the model can be estimated. There, 3(n) factorial experiments (point designs or observations) may be necessary. For small values of 'n' such as two or three, this design works well. However, when a large number of design parameters are under study, the number of design points required for a full-factorial design may become excessive. Fortunately, these quadratic polynomial approximations can be obtained by selecting an efficient design matrix using central composite designs (CCD) from design of experiments theory. Each unique point design from the CCD matrix is then conducted using computerized analysis tools (e.g. POST, CONSIZ, etc.). In the next step, least squares regression analysis is used to calculate the quadratic polynomial coefficients from the data. However, in some multidisciplinary applications involving a large number of design variables and several disciplines, the computerized performance synthesis programs may get too time consuming and expensive to run even with the use of efficient central composite designs. In such cases, it may be preferable to keep the number of design points to an absolute minimum and trade some model accuracy with cost. For this purpose, another class of experimental designs, called saturated D-optimal designs may be utilized for generating a matrix of vehicle designs. A design is called saturated when the number of design points is exactly equal to the number of terms in the model to be fitted. As a result, saturated designs require the absolute minimum number of design points ((n+1)(n+2)/s) to estimate the quadratic polynomial model coefficients. Saturated designs can be generated using the D-optimality criterion. A good saturated design should give rise to least squares estimates with minimum generalized variance.

Unal, Resit↗
DOE OSTI2015

A gyrokinetic one-dimensional scrape-off layer model of an edge-localized mode heat pulse

An electrostatic gyrokinetic-based model is applied to simulate parallel plasma transport in the scrape-off layer to a divertor plate. The authors focus on a test problem that has been studied previously, using parameters chosen to model a heat pulse driven by an edge-localized mode in JET. Previous work has used direct particle-in-cell equations with full dynamics, or Vlasov or fluid equations with only parallel dynamics. With the use of the gyrokinetic quasineutrality equation and logical sheath boundary conditions, spatial and temporal resolution requirements are no longer set by the electron Debye length and plasma frequency, respectively. This test problem also helps illustrate some of the physics contained in the Hamiltonian form of the gyrokinetic equations and some of the numerical challenges in developing an edge gyrokinetic code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Modeling Wavelength Dependent Mid-infrared (5.5–25 μm) Optical Constants of Silicate Glasses: A Genetic Algorithm Approach

Wavelength-dependent mid-infrared (400–1,800 cm -1 ; 5.56–25 μm) optical constants (real and imaginary indices of refraction; n and k) are determined using reflectance spectra at a spectral sampling of 4 cm -1 for several silicate glasses of varying SiO 2 wt% which include (a) basaltic volcanic glass from Kilauea, Hawaii, (b) synthetic andesite, (c) two synthetic dacites, (d) obsidian volcanic glass from Mount Lassen, California, (e) synthetic rhyodacite, and (f) rhyolitic volcanic glass from Mexico. Because glasses are optically isotropic, no specific orientation was required for spectral measurements, and polished glass samples were measured at random orientations using micro-FTIR spectrometer. Lorentz-Lorenz dispersion theory and Fresnel reflectance model for high symmetry materials were used to model the optical constants by optimizing oscillator parameters in modeled spectra to match laboratory spectra. A genetic algorithm (GA) approach automatically finds the natural oscillators and their parameters for each spectrum, and then uses these parameters in a non-linear least squares optimization routine. The study compared spectral parameters such as Christiansen feature, reststrahlen bands (RBs), and the peaks centered around 860–1,100 (peak 1) and 400–480 cm -1 (peak 2) of n and k to their respective SiO 2 wt% of the glasses. CF, RBs, peak 1 of n and k, and peak 2 of n shift to higher wavenumbers with increased SiO 2 wt%, whereas peak 2 of k shifts to lower wavenumbers with increased SiO 2 wt%. Derived optical constants of these glasses will improve quantitative abundance mapping of volcanic materials on the surfaces of silicate targets in the Solar System.

58 GEOSCIENCES↗
DOE OSTI2013

Degeneracies in parametrized modified gravity models

We study degeneracies between parameters in some of the widely used parametrized modified gravity models. We investigate how different observables from a future photometric weak lensing survey such as LSST, correlate the effects of these parameters and to what extent the degeneracies are broken. We also study the impact of other degenerate effects, namely massive neutrinos and some of the weak lensing systematics, on the correlations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

THE SLOAN DIGITAL SKY SURVEY QUASAR LENS SEARCH. V. FINAL CATALOG FROM THE SEVENTH DATA RELEASE

We present the final statistical sample of lensed quasars from the Sloan Digital Sky Survey (SDSS) Quasar Lens Search (SQLS). The well-defined statistical lens sample consists of 26 lensed quasars brighter than i = 19.1 and in the redshift range of 0.6 < z < 2.2 selected from 50,826 spectroscopically confirmed quasars in the SDSS Data Release 7 (DR7), where we restrict the image separation range to 1'' < {theta} < 20'' and the i-band magnitude differences in two images to be smaller than 1.25 mag. The SDSS DR7 quasar catalog also contains 36 additional lenses identified with various techniques. In addition to these lensed quasars, we have identified 81 pairs of quasars from follow-up spectroscopy, 26 of which are physically associated binary quasars. The statistical lens sample covers a wide range of image separations, redshifts, and magnitudes, and therefore is suitable for systematic studies of cosmological parameters and surveys of the structure and evolution of galaxies and quasars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Impact of Inverter-Interfaced Renewable Generation on Transient Stability at Varying Levels of Penetration: Preprint

The transient dynamics of conventional power systems are dominated by synchronous generators, and low-inertia inverters serve as the primary interface between power systems and renewable energy resources. Increasing penetration levels of inverter-interfaced generation are impacting the transient dynamics of power systems. In this paper, we attempt to quantify these impacts at different penetration levels. An elementary system including one inverter, one synchronous generator, and one load is studied under different parameter variations to assess the transient dynamics of the system. To quantify transient stability, the post-fault regions of attraction of the system are estimated by the sample-based basin stability approach with parallel computing technology. The simulation results suggest that different inverter penetration levels, inertias of the generator, inverter controller gains, and phase-locked loop controller gains have a clear impact on the regions of attraction as well as on the transient dynamics of proposed systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Compact tunable Compton x-ray source from laser-plasma accelerator and plasma mirror

We present an in-depth experimental-computational study of the parameters necessary to optimize a tunable, quasi-monoenergetic, efficient, low-background Compton backscattering (CBS) x-ray source that is based on the self-aligned combination of a laser-plasma accelerator (LPA) and a plasma mirror (PM). The main findings are (1) an LPA driven in the blowout regime by 30 TW, 30 fs laser pulses produce not only a high-quality, tunable, quasi-monoenergetic electron beam, but also a high-quality, relativistically intense (a{sub 0} ∼ 1) spent drive pulse that remains stable in profile and intensity over the LPA tuning range. (2) A thin plastic film near the gas jet exit retro-reflects the spent drive pulse efficiently into oncoming electrons to produce CBS x-rays without detectable bremsstrahlung background. Meanwhile, anomalous far-field divergence of the retro-reflected light demonstrates relativistic “denting” of the PM. Exploiting these optimized LPA and PM conditions, we demonstrate quasi-monoenergetic (50% FWHM energy spread), tunable (75–200 KeV) CBS x-rays, characteristics previously achieved only on more powerful laser systems by CBS of a split-off, counter-propagating pulse. Moreover, laser-to-x-ray photon conversion efficiency (∼6 × 10{sup −12}) exceeds that of any previous LPA-based quasi-monoenergetic Compton source. Particle-in-cell simulations agree well with the measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0

Abstract. Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. Estimates of future land use and land cover differ significantly across economic models as a result of differences in drivers, model structure, and model parameters; however, these models often rely on heuristics to determine model parameters. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. Specifically, we generate a large set of model parameter perturbations for the selected parameters and run gcamland simulations with these parameter sets over the historical period in the United States to quantify land use and land cover, determine how well the model reproduces observations, and identify parameter combinations that best replicate observations, assuming other model parameters are fixed. We also test alternate methods for forming expectations about uncertain crop yields and prices, including adaptive, perfect, linear, and hybrid approaches. In particular, we estimate parameters for six parameters used in the formation of expectations and three of seven logit exponents for the USA only. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops, landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We examine the change in model parameters as the metric of model error changes, finding that the measure of model fitness affects the choice of parameter sets. Finally, we discuss how the methodology and results used in this study could be used for other regions or economic models to improve projections of future land use and land cover change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

A comparison of two photogrammetric algorithms for the measurement of model deformation in the National Transonic Facility

A comparison was made of two photogrammetric measurement techniques which can be used for the determination of the spatial loctions of targets. One technique is known as the Direct Linear Transformation (DLT), and the other is referred to as the Bundle method. Each technique utilizes triangulation of image data from two or more cameras, but they differ in their method of determining camera parameters. While the study was performed with simulated data, the geometries, image data accuracies and other parameters were set to simulate conditions for a two-camera, photogrammetric system which will be used at the National Transonic Facility at the NASA's Langley Research Center. For the conditions studied the Bundle technique was found to have smaller errors. Both methods were sensitive to the spatial distribution of control-point targets, but this effected the accuracy of the Bundle algorithm less than that of the DLT algorithm.

Monteith, J. H.↗
NASA NTRSDate not supplied

Electric Sail Design Sensitivities

Electric Sails (E-Sails) are a promising propulsion technology that seek to enable high characteristic propellentless acceleration for spacecraft to reach distant and/or difficult to reach orbits such as rapid transit to heliopause. The E-Sail system exchanges momentum by using positively charged electrostatic tethers to repel solar wind photons to push it through space. This concept was first theorized by Pekka Janhunen in 2004 with further developments occurring including a NASA Innovative Advanced Concepts Phase 1 and Phase 2 hosted out of NASA’s Marshall Space Flight Center (MSFC). These developments led to further maturation of the overall system, and this paper is designed to help identify different design sensitivities of an integrated Electric Sail system. To approach this, a small team at MSFC took an in-house developed three degrees of freedom (3DoF) simulation tool and a trajectory modelling tool to look at different design parameters and to determine a potential ideal E-Sail configuration. An E-Sail system has different design architectures including a barbell design, hub and spoke design, and a potential hybrid solution. The barbell design features two equally massed satellites that spin around a central point in the tether system. The hub and spoke design features a large central spacecraft with small end spacecraft to aid in formation control of the overall E-Sail system. Leveraging elements from both the hub and spoke, and barbell design, a hybrid option exists where one could have a larger central mass and one or two tethers extended to a smaller end mass [2]. In summary, the hub and spoke design is the ideal configuration for E-Sail with tethers spanning kilometers to achieve the designed design characteristic acceleration of at least one mm/s2 with this architecture being the focus of this study. Different key design parameters were varied as part of this study. These parameters include the total number of tethers, the length of the tethers, spin rate, relative spacecraft mass, tether voltage, inertia per tether, and impact of slew rate changes. These results started from an internal MSFC technology demonstration mission design and then the parameters were varied with engineering judgement to ensure that the results were consistent with expected results. These were varied in the MSFC 3DoF tool and compared to baseline results to generate a candidate ideal E-Sail design system. These results were then used to help inform the mission analysis design for the system. The 3DoF trajectory optimization was performed in the Astrodynamics and Space Science Enabling Toolbox (ASSET) and utilized collocation optimization of control vector pointing with the objective function being transfer duration. A representative model of the E-Sail force was derived as a function of the Sun-pointing vector direction. This model was initialized with a zero Sun Incidence Angle (SIA) trajectory for the initial guess generation, then with a portion of the mission optimized SIA time history for fast outbound transfers. After the trajectory is hyperbolic relative to a heliocentric frame, the SIA is maintained at 0 degrees except for any needed trajectory correction maneuvers. This trajectory optimization looked at different characteristic acceleration values to analyze the impact it had on mission performance. As a result of this study, the team can best inform mission designers and technology development efforts to mature the E-Sail system. This study will allow mission designers to have defined rules-of-thumb to design an E-Sail system to meet desired mission needs as well as providing several sample mission profiles. These design drivers will inform maturation efforts on which design requirements to consider for an integrated E-Sail design.

E-Sail↗
DOE OSTI2018

Laser Wavelength and Argon Ambient Gas Pressure Effects on Metallic Plasma Emission

The effects of laser wavelength and argon ambient gas pressure on ionic and atomic emission from aluminum and copper metal plasmas has been studied. The plasmas were generated using metal targets excited with a Q-switched Nd:YAG laser operating at the first fundamental (1064 nm), second (532 nm), third (355 nm), and fourth harmonics (266 nm) with repetition rate up to 10 Hz. The spectroscopic analysis of the plasma plume emission revealed that the intensities and signal-to-noise (S/N) ratio of various neutral and ion spectral lines, small components, and trace impurities increase sharply when the fourth laser harmonic is used at a wavelength of 266 nm. Based on LTE assumption, the electron excitation temperature (T{sub e}) and electron number density (N{sub e}) of the produced plasma have been estimated from the Boltzmann plot using neutral spectral lines of Al I at 256.8, 257.5, 309.3, and 396.15 nm and Cu I at 427.58, 510.59, 570.07, and 578.58 nm and from Stark broadening width profile of Al II at 281.6 nm and Cu I at 324.75 nm, respectively. The variations of T{sub e}, N{sub e}, and emission intensities of metals as a function of laser irradiance of different laser wavelengths at 1064, 532, 355, and 266 nm were studied. The effect of the argon ambient gas pressure on the plasma parameters was also studied. The diagnostics of the produced metal plasma was undertaken using laser induced breakdown spectroscopy (LIBS).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data

Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.

42 ENGINEERING↗
DOE OSTI2021

Development of Martini 2.2 parameters for N -glycans: a case study of the HIV-1 Env glycoprotein dynamics

N-linked glycans are ubiquitous in nature and play key roles in biology. For example, glycosylation of pathogenic proteins is a common immune evasive mechanism, hampering the development of successful vaccines. Due to their chemical variability and complex dynamics, an accurate molecular understanding of glycans is still limited by the lack of effective resolution of current experimental approaches. Here, we have developed and implemented a reductive model based on the popular Martini 2.2 coarse-grained force field for the computational study of N-glycosylation. We used the HIV-1 Env as a direct applied example of a highly glycosylated protein. Finally, our results indicate that the model not only reproduces many observables in very good agreement with a fully atomistic force field but also can be extended to study large amount of glycosylation variants, a fundamental property that can aid in the development of drugs and vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Parameter Co-optimization for Hybrid Electric Vehicles Powertrain System Leveraging V2V/V2I Information

A parameter tuning based co-optimization scheme for the hybrid electric vehicles (HEV) powertrain system is designed to maximize the fuel efficiency. The optimization controlled input parameters are chosen based on sensitivity study of powertrain control parameters. The vehicle to vehicle (V2V) and vehicle to infrastructure information is another optimization input, to have the driving conditions taking in to considerations for maximizing fuel efficiency. The catalyst temperature is considered as an additional constraint as the speed to reach light-off temperature should not decrease during optimized operation. Neural network is used to develop a simplified yet equivalent model for the optimization problem model. We have achieved an average of 9.22% fuel savings for a random driving cycle on a Toyota Prius test model.

V2V, Cooptimization↗
DOE OSTI2018

A Sensitivity Study of the Impact of Installation Parameters and System Configuration on the Performance of Bifacial PV Arrays

In this paper, we present the effect of installation parameters (tilt angle, height above ground, and albedo) on the bifacial gain and energy yield of three south-facing photovoltaic (PV) system configurations: a single module, a row of five modules, and five rows of five modules utilizing RADIANCE-based ray tracing model. We show that height and albedo have a direct impact on the performance of bifacial systems. However, the impact of the tilt angle is more complicated. Seasonal optimum tilt angles are dependent on parameters such as height, albedo, size of the system, weather conditions, and time of the year. For a single bifacial module installed in Albuquerque, NM, USA (35 degrees N) with a reasonable clearance (~1 m) from the ground, the seasonal optimum tilt angle is lowest (~5 degrees) for the summer solstice and highest (~65 degrees) for the winter solstice. For larger systems, seasonal optimum tilt angles are usually higher and can be up to 20 degrees greater than that for a single module system. Annual simulations also indicate that for larger fixed-tilt systems installed on a highly reflective ground (such as snow or a white roofing material with an albedo of ~81%), the optimum tilt angle is higher than the optimum angle of the smaller size systems. We also show that modules in larger scale systems generate lower energy due to horizon blocking and large shadowing area cast by the modules on the ground. For albedo of 21%, the center module in a large array generates up to 7% less energy than a single bifacial module. To validate our model, we utilize measured data from Sandia National Laboratories' fixed-tilt bifacial PV testbed and compare it with our simulations.

14 SOLAR ENERGY↗
DOE OSTI2014

A study of the impact of scheduling parameters in heterogeneous computing environments

This paper describes a tool for exploring system scheduler parameter settings in a heterogeneous computing environment. Through the coupling of simulation and optimization techniques, this work investigates optimal scheduling intervals, the impact of job arrival prediction on scheduling, as well as how to best apply fair use policies. The developed simulation framework is quick and modular, enabling decision makers to further explore decisions in real-time regarding scheduling policies or parameter changes.

Powers, Sarah↗