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At least 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Sensitivity of Photolysis Frequencies and Key Tropospheric Oxidants in a Global Model to Cloud Vertical Distributions and Optical Properties

As a follow-up study to our recent assessment of the radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties in a global 3-D chemical transport model (GEOS4-Chem CTM). GEOS-Chem was driven with a series of meteorological archives (GEOS1-STRAT, GEOS-3 and GEOS-4) generated by the NASA Goddard Earth Observing System data assimilation system, which have significantly different cloud optical depths (CODs) and vertical distributions. Clouds in GEOS1-STRAT and GEOS-3 have more similar vertical distributions while those in GEOS-4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. Model simulations with each of the three cloud distributions all show that the change in the global burden of O3 due to clouds is less than 5%. Model perturbation experiments with GEOS-3, where the magnitude of 3-D CODs are progressively varied by -100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2) and OH concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs due to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the UV wavelength. Our results have important implications for model intercomparisons and climate feedback on tropospheric photochemistry.

Liu, Hongyu↗
DOE OSTI2020

Sensitivity Studies of Premixed Flame Response to Transverse, High Frequency Disturbances

This study analyzes the response of premixed flames to high frequency transverse acoustic disturbances. A significant body of experiment, modeling and simulation efforts has been performed to understand the response of the spatially integrated heat release of premixed flames to low-frequency disturbances. These studies quantified this sensitivity through the Flame Transfer Function (FTF), as the global heat release is the key quantity influencing thermoacoustic stability for acoustically compact flames. Recent efforts have expanded these models to consider high-frequency acoustic disturbances, and the sensitivity of premixed flames through the Rayleigh integral (RI). The full Rayleigh Integral, as opposed to simply the spatially integrated heat release, must be considered in these cases where the flame is not acoustically compact. Prior modeling studies considered several effects - stability of axisymmetric flames centered in a cylindrical combustion chamber and the effect of flame offset from the combustor axis and the effect of mean flame asymmetries in the flame centered in the combustor. These studies showed that the flame's stability was sensitive to all these parameters, as well as to the transverse mode in question. In this paper, we quantify these different parametric sensitivities of premixed flame stability in the presence of high-frequency transverse acoustic modes - specifically sensitivity to flame length and nozzle location within the acoustic mode shape for 2 different transverse modes. The sensitivity of the RI to these control parameters provides an improved understanding of which flame parameters are critical to improve the overall thermoacoustic stability of the system.

Acharya, Vishal S.↗
DOE OSTI2022

Towards a Unified Setup to Simulate Mid‐Latitude and Tropical Mesoscale Convective Systems at Kilometer‐Scales

Abstract Mesoscale convective systems (MCSs) are the main source of precipitation in the tropics and parts of the mid‐latitudes and are responsible for high‐impact weather worldwide. Studies showed that deficiencies in simulating mid‐latitude MCSs in state‐of‐the‐art climate models can be alleviated by kilometer‐scale models. However, whether these models can also improve tropical MCSs and whether we can find model settings that perform well in both regions is understudied. We take advantage of high‐quality MCS observations collected over the Atmospheric Radiation Measurement (ARM) facilities in the US Southern Great Plains (SGP) and the Amazon basin near Manaus (MAO) to evaluate a perturbed physics ensemble of simulated MCSs with 4 km horizontal grid spacing. A new model evaluation method is developed that enables to distinguish biases stemming from spatiotemporal displacements of MCSs from biases in their reflectivity and cloud shield. Amazon MCSs are similarly well simulated across these evaluation metrics than SGP MCSs despite the challenges anticipated from weaker large‐scale forcing in the tropics. Generally, SGP MCSs are more sensitive to the choice of model microphysics, while Amazon cases are more sensitive to the planetary boundary layer (PBL) scheme. Although our tested model physics combinations had strengths and weaknesses, combinations that performed well for SGP simulations result in worse results in the Amazon basin and vice versa. However, we identified model settings that perform well at both locations, which include the Thompson and Morrison microphysics coupled with the Yonsei University (YSU) PBL scheme and the Thompson scheme coupled with the Mellor‐Yamada‐Janjic PBL scheme.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Approach for Uncertainty Propagation and Robust Design in CFD Using Sensitivity Derivatives

This paper presents an implementation of the approximate statistical moment method for uncertainty propagation and robust optimization for a quasi 1-D Euler CFD (computational fluid dynamics) code. Given uncertainties in statistically independent, random, normally distributed input variables, a first- and second-order statistical moment matching procedure is performed to approximate the uncertainty in the CFD output. Efficient calculation of both first- and second-order sensitivity derivatives is required. In order to assess the validity of the approximations, the moments are compared with statistical moments generated through Monte Carlo simulations. The uncertainties in the CFD input variables are also incorporated into a robust optimization procedure. For this optimization, statistical moments involving first-order sensitivity derivatives appear in the objective function and system constraints. Second-order sensitivity derivatives are used in a gradient-based search to successfully execute a robust optimization. The approximate methods used throughout the analyses are found to be valid when considering robustness about input parameter mean values.

Putko, Michele M.↗
NASA NTRS1999

DSMC Simulation of Shock/Shock Interactions: Emphasis on Type IV Interactions

This paper presents the results of a numerical study of shock/shock interactions that include both the Edney type IV and type III interactions, with emphasis on the type IV interactions. Computations are made using the direct simulation Monte Carlo (DSMC) method of Bird for Mach 10 air flow, as produced in the ONERA R5Ch low-density wind tunnel. The simulations include the flow about a shock generator which creates a relatively weak oblique shock that impinges on a much stronger cylinder bow shock. The sensitivity and characteristics of the interactions are examined by varying the horizontal distance separating the shock generator leading edge and cylinder. Results of the simulation for one separation distance are compared with wind tunnel measurements. Comparisons are made for surface heating and pressure and for flow-field values of density and rotational temperatures, as obtained with the Dual-line Coherent Anti-Stokes Scattering (DL-CARS) technique. The comparisons between experiment and calculation yield a consistent description of the shock interaction features and a consistent description of the surface heating and pressure distributions, with the exception of the peak values-the computed values being greater than the measured values.

Moss, J. N.↗
NASA NTRS2002

Approach for Input Uncertainty Propagation and Robust Design in CFD Using Sensitivity Derivatives

An implementation of the approximate statistical moment method for uncertainty propagation and robust optimization for quasi 3-D Euler CFD code is presented. Given uncertainties in statistically independent, random, normally distributed input variables, first- and second-order statistical moment procedures are performed to approximate the uncertainty in the CFD output. Efficient calculation of both first- and second-order sensitivity derivatives is required. In order to assess the validity of the approximations, these moments are compared with statistical moments generated through Monte Carlo simulations. The uncertainties in the CFD input variables are also incorporated into a robust optimization procedure. For this optimization, statistical moments involving first-order sensitivity derivatives appear in the objective function and system constraints. Second-order sensitivity derivatives are used in a gradient-based search to successfully execute a robust optimization. The approximate methods used throughout the analyses are found to be valid when considering robustness about input parameter mean values.

Putko, Michele M.↗
NASA NTRS1999

Electrostatic Discharge Effects on Thin Film Resistors

Recently, open circuit failures of individual elements in thin film resistor networks have been attributed to electrostatic discharge (ESD) effects. This paper will discuss the investigation that came to this conclusion and subsequent experimentation intended to characterize design factors that affect the sensitivity of resistor elements to ESD. The ESD testing was performed using the standard human body model simulation. Some of the design elements to be evaluated were: trace width, trace length (and thus width to length ratio), specific resistivity of the trace (ohms per square) and resistance value. However, once the experiments were in progress, it was realized that the ESD sensitivity of most of the complex patterns under evaluation was determined by other design and process factors such as trace shape and termination pad spacing. This paper includes pictorial examples of representative ESD failure sites, and provides some options for designing thin film resistors that are ESD resistant. The risks of ESD damage are assessed and handling precautions suggested.

Sampson, Michael J.↗
DOE OSTI2025

Advancing Multiscale Simulation of Plasma-Surface Interfaces

We report the development of an atomistic-informed, surface-state-dependent predictive model for particle exchange in a carbon-tungsten plasma-surface interface. The predictive model uses machine learning (ML) techniques to learn the energy and angular distributions for particle exchange and rate functions for surface state evolution from molecular dynamics simulations of cumulative bombardment of tungsten by energetic carbon ions. Each predictive component is sensitive to the energy and trajectory of incident plasma species and the surface state. The surface state is represented by a set of surface state descriptors, which were derived from the atomistic surface state for each independent carbon bombardment event. These descriptors are representative of the composition and degree of amorphization of the outermost angstrom of surface material and were chosen to optimize predictive performance for particle exchange at the interface. The distributions for particle exchange (reflection/sputtering) are demonstrated to vary with each surface state descriptor, motivating the development of surface-state-dependent particle exchange models for plasma simulations. The performance of various ML methods was compared, including polynomial quantile regression, artificial neural networks, k-nearest neighbors, and random forest algorithms, with polynomial regression performing the best for interpolation and extrapolation of learned relationships. In addition to the particle exchange model, a neutral network was developed and used to identify data sufficiency throughout surface descriptor space, which will enable real-time feedback during future data production to ensure data is produced where it is most needed, and we provide commentary on improvements to the data production workflow for future endeavors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2000

Sensitivity of Age-of-Air Calculations to the Choice of Advection Scheme

The age of air has recently emerged as a diagnostic of atmospheric transport unaffected by chemical parameterizations, and the features in the age distributions computed in models have been interpreted in terms of the models' large-scale circulation field. This study shows, however, that in addition to the simulated large-scale circulation, three-dimensional age calculations can also be affected by the choice of advection scheme employed in solving the tracer continuity equation, Specifically, using the 3.0deg latitude X 3.6deg longitude and 40 vertical level version of the Geophysical Fluid Dynamics Laboratory SKYHI GCM and six online transport schemes ranging from Eulerian through semi-Lagrangian to fully Lagrangian, it will be demonstrated that the oldest ages are obtained using the nondiffusive centered-difference schemes while the youngest ages are computed with a semi-Lagrangian transport (SLT) scheme. The centered- difference schemes are capable of producing ages older than 10 years in the mesosphere, thus eliminating the "young bias" found in previous age-of-air calculations. At this stage, only limited intuitive explanations can be advanced for this sensitivity of age-of-air calculations to the choice of advection scheme, In particular, age distributions computed online with the National Center for Atmospheric Research Community Climate Model (MACCM3) using different varieties of the SLT scheme are substantially older than the SKYHI SLT distribution. The different varieties, including a noninterpolating-in-the-vertical version (which is essentially centered-difference in the vertical), also produce a narrower range of age distributions than the suite of advection schemes employed in the SKYHI model. While additional MACCM3 experiments with a wider range of schemes would be necessary to provide more definitive insights, the older and less variable MACCM3 age distributions can plausibly be interpreted as being due to the semi-implicit semi-Lagrangian dynamics employed in the MACCM3. This type of dynamical core (employed with a 60-min time step) is likely to reduce SLT's interpolation errors that are compounded by the short-term variability characteristic of the explicit centered-difference dynamics employed in the SKYHI model (time step of 3 min). In the extreme case of a very slowly varying circulation, the choice of advection scheme has no effect on two-dimensional (latitude-height) age-of-air calculations, owing to the smooth nature of the transport circulation in 2D models. These results suggest that nondiffusive schemes may be the preferred choice for multiyear simulations of tracers not overly sensitive to the requirement of monotonicity (this category includes many greenhouse gases). At the same time, age-of-air calculations offer a simple quantitative diagnostic of a scheme's long-term diffusive properties and may help in the evaluation of dynamical cores in multiyear integrations. On the other hand, the sensitivity of the computed ages to the model numerics calls for caution in using age of air as a diagnostic of a GCM's large-scale circulation field.

Eluszkiewicz, Janusz↗
DOE OSTI2022

Data-Enabled Predictive Control for Building HVAC Systems

Model predictive control is widely used as a control technology for the computation of optimal control inputs of building heating, ventilating, and air conditioning (HVAC) systems. However, both the benefits and widespread adoption of model predictive control (MPC) are hindered by the effort of model creation, calibration, and accuracy of the predictions. In this paper, we apply the data-enabled predictive control (DeePC) algorithm for designing controls for building HVAC systems. The algorithm solely depends on input/output data from the system to predict future state trajectories without the need for system identification. The algorithm relies on the idea that a vector space of all input–output trajectories of a discrete-time linear time-invariant (LTI) system is spanned by time-shifts of a single measured trajectory, given the input signal is persistently exciting. Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated building modeled in EnergyPlus is a modified commercial large office prototype building served by an air handling unit-variable air volume HVAC system. Temperature setpoints of zones are used as control variables to minimize the HVAC energy cost of the building considering a time-of-use electricity rate structure. Furthermore, sensitivity analysis is conducted to gain insights into the effect of parameter tuning on DeePC performance. Simulation results are used to illustrate the performance of the algorithm and compare the algorithm with model-based MPC and occupancy-based setpoint controller. Overall, DeePC achieves similar performance compared to MPC for lower engineering effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2018

Reynolds-Stress Budgets in an Impinging Shock Wave/Boundary-Layer Interaction

Implicit large-eddy simulation (ILES) of a shock wave/boundary-layer interaction (SBLI) was performed. Comparisons with experimental data showed a sensitivity of the current prediction to the modeling of the sidewalls. This was found to be common among various computational studies in the literature where periodic boundary conditions were used in the spanwise direction, as was the case in the present work. Thus, although the experiment was quasi-two-dimensional, the present simulation was determined to be two-dimensional. Quantities present in the exact equation of the Reynolds-stress transport, i.e., production, molecular diffusion, turbulent transport, pressure diffusion, pressure strain, dissipation, and turbulent mass flux were calculated. Reynolds-stress budgets were compared with past large-eddy simulation and direct numerical simulation datasets in the undisturbed portion of the turbulent boundary layer to validate the current approach. The budgets in SBLI showed the growth in the production term for the primary normal stress and energy transfer mechanism was led by the pressure strain term in the secondary normal stresses. The pressure diffusion term, commonly assumed as negligible by turbulence model developers, was shown to be small but non-zero in the normal stress budgets, however it played a key role in the primary shear stress budget.

shock wave/boundary-layer interactio↗
DOE OSTI2022

Simulation-guided analysis of resonant soft X-ray scattering for determining the microstructure of triblock copolymers

Resonant soft X-ray scattering (RSoXS) probes structure with chemical sensitivity that is useful for determining the morphology of multiblock copolymers. However, the hyperspectral scattering data produced by this technique can be challenging to interpret. Here, in this study, we use computational scattering simulations to extract the microstructure of a model triblock copolymer from the energy-dependent scattering from RSoXS. An ABC triblock terpolymer formed from poly(4-methylcaprolactone) (P4MCL), poly(2,2,2-trifluoroethylacrylate) (PTFEA), and poly (dodecylacrylate) (PDDA), P4MCL-block-PTFEA-block-PDDA, was synthesized as the model triblock system. Through quantitative evaluation of simulated scattering data from a physics-informed set of candidate structure models against experimental RSoXS data, we find the best agreement with hexagonally packed core–shell cylinders. This result is also consistent with electron-density reconstruction from hard X-ray scattering data evaluated against electron-density maps generated with the same model set. These results demonstrate the utility of simulation-guided scattering analysis to study complex microstructures that are challenging to image by microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

LANDSAT-D investigations in snow hydrology

The sample LANDSAT-4 TM tape (7 bands) of NE Arkansas/Tennessee area was received and displayed. Snow reflectance in all 6 TM reflective bands, i.e. 1, 2, 3, 4, 5, and 7 was simulated, using Wiscombe and Warren's (1980) delta-Eddington model. Snow reflectance in bands 4, 5, and 7 appear sensitive to grain size. One of the objectives is to interpret surface optical grain size of snow, for spectral extension of albedo. While TM data of the study area are not received, simulation results are encouraging. It also appears that the TM filters resemble a "square-wave" closely enough to permit assuming a square-wave in calculations. Integrated band reflectance over the actual response functions was simulated, using sensor data supplied by Santa Barbara Research Center. Differences between integrating over the actual response functions and the equivalent square wave were negligible.

Dozier, J.↗
NASA NTRS2012

Implementation of a Transition Model in a NASA Code and Validation Using Heat Transfer Data on a Turbine Blade

The purpose of this report is to summarize and document the work done to enable a NASA CFD code to model laminar-turbulent transition process on an isolated turbine blade. The ultimate purpose of the present work is to down-select a transition model that would allow the flow simulation of a variable speed power turbine to be accurately performed. The flow modeling in its final form will account for the blade row interactions and their effects on transition which would lead to accurate accounting for losses. The present work only concerns itself with steady flows of variable inlet turbulence. The low Reynolds number k- model of Wilcox and a modified version of the same model will be used for modeling of transition on experimentally measured blade pressure and heat transfer. It will be shown that the k- model and its modified variant fail to simulate the transition with any degree of accuracy. A case is thus made for the adoption of more accurate transition models. Three-equation models based on the work of Mayle on Laminar Kinetic Energy were explored. The three-equation model of Walters and Leylek was thought to be in a relatively mature state of development and was implemented in the Glenn-HT code. Two-dimensional heat transfer predictions of flat plate flow and two-dimensional and three-dimensional heat transfer predictions on a turbine blade were performed and reported herein. Surface heat transfer rate serves as sensitive indicator of transition. With the newly implemented model, it was shown that the simulation of transition process is much improved over the baseline k- model for the single Reynolds number and pressure ratio attempted; while agreement with heat transfer data became more satisfactory. Armed with the new transition model, total-pressure losses of computed three-dimensional flow of E3 tip section cascade were compared to the experimental data for a range of incidence angles. The results obtained, form a partial loss bucket for the chosen blade. In time the loss bucket will be populated with losses at additional incidences. Results obtained thus far will be discussed herein.

Ameri, Ali A.↗
DOE OSTI2023

Physics-informed machine learning for fault-leakage reduced-order modeling

Geologic carbon storage (GCS) is a promising technology for mitigating CO 2 emissions. The overall success of GCS depends on safe operations that are informed by risk assessment and have proper mitigation plans in place. Performing quantitative probabilistic risk assessment for a GCS site using traditional reservoir simulators can be challenging due to the high computational costs. To overcome this challenge, the US Department of Energy’s National Risk Assessment Partnership (NRAP) project has developed an integrated assessment modeling approach that utilizes computationally efficient reduced-order models (ROM) for simulating various parts of a GCS storage site to quantify uncertainty. Here, in this study, we develop a reduced-order model for fault leakage risk assessment. We use a deep learning approach to build the reduced-order model. We perform a sensitivity analysis and find that the deep learning model yields high accuracy with a much smaller computational cost than full-physics simulation. We also evaluate the performance of the model in scenarios where simulations are not possible to run, providing analysis not previously performed in fault-leakage ROM analyses. Based on a sensitivity analysis of the model, we suggest a simplified conceptual model for fault leakage and site monitoring.

58 GEOSCIENCES↗
NASA NTRS1997

Fatigue Reliability of Gas Turbine Engine Structures

The results of an investigation are described for fatigue reliability in engine structures. The description consists of two parts. Part 1 is for method development. Part 2 is a specific case study. In Part 1, the essential concepts and practical approaches to damage tolerance design in the gas turbine industry are summarized. These have evolved over the years in response to flight safety certification requirements. The effect of Non-Destructive Evaluation (NDE) methods on these methods is also reviewed. Assessment methods based on probabilistic fracture mechanics, with regard to both crack initiation and crack growth, are outlined. Limit state modeling techniques from structural reliability theory are shown to be appropriate for application to this problem, for both individual failure mode and system-level assessment. In Part 2, the results of a case study for the high pressure turbine of a turboprop engine are described. The response surface approach is used to construct a fatigue performance function. This performance function is used with the First Order Reliability Method (FORM) to determine the probability of failure and the sensitivity of the fatigue life to the engine parameters for the first stage disk rim of the two stage turbine. A hybrid combination of regression and Monte Carlo simulation is to use incorporate time dependent random variables. System reliability is used to determine the system probability of failure, and the sensitivity of the system fatigue life to the engine parameters of the high pressure turbine. 'ne variation in the primary hot gas and secondary cooling air, the uncertainty of the complex mission loading, and the scatter in the material data are considered.

Cruse, Thomas A.↗
DOE OSTI2021

Global Sensitivity Analysis of a Reactive Transport Model for Mineral Scale Formation During Hydraulic Fracturing

Injection of water-based hydraulic fracturing fluid (HFF) into tight shale gas/oil formations can increase formation permeability and enhance production rates, but this process frequently causes mineral scale formation that can occlude pore space and hinder flow. To identify the most important factors that control the formation of mineral scales, we applied a novel global sensitivity analysis method—distance-based generalized sensitivity analysis (DGSA)—to a reactive transport model (RTM) that was previously built and calibrated to simulate precipitation of barite [BaSO4] and iron (hydr)oxide [Fe(OH) 3 ] in shale matrices and on fracture surfaces. Reactive transport simulations were run with model parameters randomly sampled based on assigned uncertainties. Modeling results for barite and Fe(OH)3 formation were clustered using machine-learning algorithms. A list of ranked critical input parameters was obtained after statistical quantification of cumulative distribution functions of input parameters. We found that barite formation is most sensitive to the rate of sulfate ion generation, which is determined by the pyrite dissolution rate coefficient and oxidant availability. In addition, barite formation is sensitive to the initial amounts of barite in HFF and shale, followed by barite thermodynamics/kinetics. For Fe(OH) 3 formation, the ranked factors are Fe(OH)3 precipitation rate coefficients, initial HFF pH, initial Fe(OH) 3 amount in HFF, and oxidant availability. Overall, our results provide insights into managing mineral scale formation during hydraulic fracturing to enhance production. Meanwhile, this study serves as an example of global sensitivity analysis of RTMs using the efficient, straightforward, and open-source DGSA method.

58 GEOSCIENCES↗
DOE OSTI2023

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗