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The City Decision Analysis at Any Scale Workshop was held February 17-18, 2021. This brochure was created to provide participants with a collection of tools and resources that support planning and implementation of clean energy goals for communities and businesses.
Propane powers nearly 60,000 vehicles in the United States. Fleets around the United States have successfully implemented propane vehicles in many types of applications, including school buses, shuttle buses, step vans, and law enforcement vehicles. Propane is also frequently used in off-road applications, such as forklifts, commercial landscape mowers and equipment, and other farm equipment. The advantages of propane include its domestic availability, performance, and emissions benefits.
This paper presents an initial study of the convergence properties of an iterative algorithm for computing the burnup distribution in a pebble bed reactor (PBR) in its equilibrium core condition. The algorithm is implemented in the Griffin code. Griffin is a reactor multiphysics analysis application jointly developed by Idaho National Laboratory (INL) and Argonne National Laboratory (ANL). Griffin’s PBR algorithm is discussed and simulation data are presented. An alternative matrix formulation of the algorithm is presented that facilitates analysis of the iterative algorithm. The dependence of the spectral radius of the iterative algorithm on operational and discretization parameters is investigated.
This paper will discuss the application of gamma spectroscopy systems for analysis of environmental media samples for parents and daughter progeny of the Natural Uranium and Thorium Decay Series radionuclides. The concentrations and relative ratios of naturally occurring isotopes are used to confirm the presence of FUSRAP-related wastes and for understanding the associated potential dose and health risks. Focus will be given to lessons learned from the set-up and operation of onsite gamma spectroscopy laboratories used to provide stakeholders with defensible and timely results to support FUSRAP site investigations and remediation including adaptive survey design implementation, physical remediation and waste transport, and confirmatory final status survey activities. This paper focuses on the potential impacts to gamma spectroscopy measurement accuracy from the following: - Bias caused by sample matrix effects as well as use of different library reference values between performance evaluation study providers and testing laboratories; - Use of calibration sources with limited energy ranges, and; - Selection of available alternative isotopic decay reference data for the input of line energies and their intensities. These lessons learned include discussing how inter-laboratory measurement differences from blind performance evaluation samples are affected by the manufacturer's measurement method, including equilibrium assumptions; the isotope decay information source library used by the study provider and participating laboratories; and calibration source geometry/density variances from actual sample conditions. Any of these factors can significantly impact the accuracy of reported results data. Deepening the reader's understanding of the various factors that impact the accuracy, interpretation, and overall usability of gamma spectroscopy results data from laboratories will help ensure defensible decision-making and cost-effective mission implementation within FUSRAP and similar remediation programs. (authors)
Large Eddy Simulations (LES) are performed to compute the sensitivity of a conventional (A-2) and an alternate bio-jet (C-1) fuel to Lean Blowout (LBO). A realistic aviation gas turbine engine combustor configuration is considered. Reliable experimental LBO data and OH* chemiluminescence data for the conventional and alternate jet fuel in the combustor configuration have recently become available. The present work utilizes a highly automated, on-the-fly meshing strategy, along with adaptive mesh refinement, to demonstrate the feasibility of capturing the realistic combustion processes. A Lagrangian framework, with initial conditions specified using measurements of spray statistics, is used to model the fuel spray. Newly developed compact reaction mechanisms based on fuel surrogates are validated for the A-2 and the C-1 fuels. The compact reaction mechanisms are implemented using a detailed finite rate chemistry solver. Spray statistics computed by the present LES simulations compare well with available measurements at stable flame conditions near the lean blowout limit. The computed shape of the stable flame as represented by line integrated OH concentrations compares well with the experimental OH* chemiluminescence data. Lean blowout is reached by gradually decreasing the fuel flow rate in the computations, similar to that in the experiments. The results of the LES simulations effectively capture the fuel composition effects and estimate the sensitivity of the LBO limits to the fuel type. The computed trends in LBO limits agree within engineering accuracy with the experimental results for conventional and alternative aviation fuels. The methodology for predicting the fuel composition effects on the lean blowout limits in a fully resolved realistic, complex combustor is established for the first time.
Hydrothermal liquefaction (HTL) has potential for converting abundant wet organic wastes into renewable fuels. Because HTL consists of a complex reaction network, deterministic, physics-based prediction of its biocrude yield is prohibitively difficult. Data-driven methods provide an alternative to the physics-based approach; however, rigorous testing must be performed to ensure the accuracy of predictions made by data-driven methods. To this end, a data set was assembled consisting of 570 data points appearing in the open literature. The data set was divided into training, validation, and test sub-sets and used for evaluating different machine learning regression approaches to predict biocrude yield. Among the tested algorithms, Random Forest and eXtreme Gradient Boosting (XGBoost) predicted biocrude yields in a test set that had not been used for training with the greatest accuracy, with root mean square errors (RMSE) of 8.34 and 8.57, respectively. Further refinement of the Random Forest model reduced its RMSE to 8.07. In comparison, predictions of a series of literature models resulted in RMSE ranging from 9.16 in the most accurate case to 27.6 in the least accurate; most literature models yielded RMSE values > 10. Using biocrude yield predictions from the most accurate Random Forest model and a probabilistic economic analysis found that the model accuracy is sufficient to prioritize allocation of resources based on projected minimum fuel selling price. In our report the models and analysis represent a major advance in the ability to use readily available data to predict biocrude yields on new feedstocks that have not previously been studied.
A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi & Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs.
This document compiles a comprehensive list of publications supported by, or related to, National Aeronautics and Space Administration Grant NSG-3048, entitled "Alternatives for Jet Engine Control". Dr. Kurt Seldner was the original Technical Officer for the grant, at Lewis Research Center. Dr. Bruce Lehtinen was the final Technical Officer. At the University of Notre Dame, Drs. Michael K. Sain and R. Jeffrey Leake were the original Project Directors, with Dr. Sain becoming the final Project Director. Publications cover work over a ten-year period. The Final Report is divided into two parts. Volume i, "Modelling and Control Design with Jet Engine Data", follows in this report. Volume 2, "Modelling and Control Design with Tensors", has been bound separately.
Abstract Modern cosmological simulations have reached the trillion-element scale, rendering data storage and subsequent analysis formidable tasks. To address this circumstance, we present a new MPI-parallel approach for analysis of simulation data while the simulation runs, as an alternative to the traditional workflow consisting of periodically saving large data sets to disk for subsequent ‘offline’ analysis. We demonstrate this approach in the compressible gasdynamics/ N -body code Nyx, a hybrid $\mbox{MPI}+\mbox{OpenMP}$ MPI + OpenMP code based on the BoxLib framework, used for large-scale cosmological simulations. We have enabled on-the-fly workflows in two different ways: one is a straightforward approach consisting of all MPI processes periodically halting the main simulation and analyzing each component of data that they own (‘ in situ ’). The other consists of partitioning processes into disjoint MPI groups, with one performing the simulation and periodically sending data to the other ‘sidecar’ group, which post-processes it while the simulation continues (‘in-transit’). The two groups execute their tasks asynchronously, stopping only to synchronize when a new set of simulation data needs to be analyzed. For both the in situ and in-transit approaches, we experiment with two different analysis suites with distinct performance behavior: one which finds dark matter halos in the simulation using merge trees to calculate the mass contained within iso-density contours, and another which calculates probability distribution functions and power spectra of various fields in the simulation. Both are common analysis tasks for cosmology, and both result in summary statistics significantly smaller than the original data set. We study the behavior of each type of analysis in each workflow in order to determine the optimal configuration for the different data analysis algorithms.
This 4-month feasibility study assessed the options, trade-offs and major issues in using National Ignition Facility (NIF) and Advanced Radiographic Capability (ARC)-class laser beams for multipulse MeV x-ray and neutron radiography of high explosives (HE) driven experiments. It was performed in close collaboration with a second FS evaluating future HE radiography requirements and expected laser-based source data quality with respect to existing and alternate radiography sources. The study first reviewed the existing published data on MeV x-ray and neutron sources compared to requirements on yield (10 14 /sr for X-rays, > 10 13 /sr for neutrons), spot size (< 1 mm) and duration (< 20 ns). For MeV neutron sources, the preferred options are DTfilled exploding pusher targets or stagnating DT plasmas, each source requiring 50 kJ level. few ns beam irradiation at 0.5 or 0.35 micron wavelength. The preferred X-ray MeV source option to be fully assessed by a follow-up SI is an angularly and temporally-multiplexed multi-burst version of a Bremsstrahlung source (Courtois et al. 2011) irradiated by up to 7 10 ps, kJ-class 1 micron wavelength lasers beams. This multi-burst laser mode, submitted as an ROI and patent, should increase final laser optics damage energy thresholds based on 2 pulse tests and hence allow near full extraction of the 15 kJ of 1 micron laser energy available on a NIF beamline. Hydrodynamic simulations were used to evaluate the effects of preceding pulse irradiation on target integrity, and show that this can be mitigated by using 3D structured targets.
Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of predefined “features” with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Some embodiments may provide viewing, creating, and manipulating of multiple versions of a solar collector layout design for a particular installation worksite. The use of versions may allow analysis of alternative layouts, alternative feature classifications, and cost and performance data corresponding to alternative design choices. Version summary information providing a representative comparison between versions across a number of dimensions may be provided.
Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre-defined “features” with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Some embodiments may provide viewing, creating, and manipulating of multiple versions of a solar collector layout design for a particular installation worksite. The use of versions may allow analysis of alternative layouts, alternative feature classifications, and cost and performance data corresponding to alternative design choices. Version summary information providing a representative comparison between versions across a number of dimensions may be provided.
Data and information in the area of advanced energy conversion systems for industrial congeneration applications in the 1985-2000 time period was studied. Six current and thirty-one advanced energy conversion systems were defined and combined with appropriate balance-of-plant equipment. Twenty-six industrial processes were selected from among the high energy consuming industries to serve as a framework for the study. Each conversion system was analyzed as a cogenerator with each industrial plant. Fuel consumption, costs, and environmental intrusion were evaluated and compared to corresponding traditional values. Various cogeneration strategies were analyzed and both topping and bottoming (using industrial by-product heat) applications were included. The advanced energy conversion technologies indicated reduced fuel consumption, costs, and emissions. Typically fuel energy savings of 10 to 25 percent were predicted compared to traditional on-site furnaces and utility electricity. With the variety of industrial requirements, each advanced technology had attractive applications. Overall, fuel cells indicated the greatest fuel energy savings and emission reductions. Gas turbines and combined cycles indicated high overall annual cost savings. Steam turbines and gas turbines produced high estimated returns. In some applications, diesels were most efficient. The advanced technologies used coal-derived fuels, or coal with advanced fluid bed combustion or on-site gasification systems.
Demagnetization temperature of a linear alternator (LA) can be accurately predicted through an analytical Maxwell model. The M-H characteristics of the alternator magnets must be known. Vendor data are given for cube-shaped magnets, and the shape of a LA magnet may affect its magnetic properties. At GRC, M-H data are directly measured for each LA magnet. This method was validated using TDC alternator tests on the Alternator Test Rig. The analytical Maxwell modeling was utilized on a different style linear alternator to predict demagnetization temperatures for the Advanced Stirling Convertor.
The present Phase 2 small business innovation research study was designed to address issues related to scalp-recorded event-related potential (ERP) indices of mental workload and to transition this technology from the laboratory to cockpit simulator environments for use as a systems engineering tool. The project involved five main tasks: (1) Two laboratory studies confirmed the generality of the ERP indices of workload obtained in the Phase 1 study and revealed two additional ERP components related to workload. (2) A task analysis' of flight scenarios and pilot tasks in the Advanced Concepts Flight Simulator (ACFS) defined cockpit events (i.e., displays, messages, alarms) that would be expected to elicit ERPs related to workload. (3) Software was developed to support ERP data analysis. An existing ARD-proprietary package of ERP data analysis routines was upgraded, new graphics routines were developed to enhance interactive data analysis, and routines were developed to compare alternative single-trial analysis techniques using simulated ERP data. (4) Working in conjunction with NASA Langley research scientists and simulator engineers, preparations were made for an ACFS validation study of ERP measures of workload. (5) A design specification was developed for a general purpose, computerized, workload assessment system that can function in simulators such as the ACFS.
Current time-dependent CFD simulations produce very large multi-dimensional data sets at each time step. The visual analysis of computational results are traditionally performed by post processing the static data on graphics workstations. We present results from an alternate approach in which we analyze the simulation data in situ on each processing node at the time of simulation. The locally analyzed results, usually more economical and in a reduced form, are then combined and sent back for visualization on a graphics workstation.
Edge data of a measured surface map of a circular optic result in large variance or "spectral leakage" behavior in the corresponding Power Spectral Density (PSD) data. In this paper we present two new, alternative methods for reducing such variance in the PSD data by replacing the zeros outside the circular area of a surface map by non-zero values either obtained from a PSD fit (method 1) or taken from the inside of the circular area (method 2).
Architectural and hyper-parameter design choices can influence deep-learner (DL) model fidelity but can also be affected by malformed training and validation data. However, practitioners may spend significant time refining layers and hyper-parameters before discovering that distorted training data was impeding training progress. We found that an evolutionary algorithm (EA) can be used to diagnose this kind of DL problem. An EA evaluated thousands of DL configurations on Summit that yielded no overall improvement in DL performance, which suggested problems with the training and validation data. We suspected that Contrast Limited Adaptive Histogram Equalization (CLAHE) enhancement that was applied to previously generated digital surface models (DSMs), for which we were training DLs to find errors, had damaged the training data. Subsequent runs with an alternative global normalization yielded significantly improved DL performance. However, the DL Intersection Over Union (IOU) still exhibited consistent sub-par performance, which suggested further problems with the training data and DL approach. Nonetheless, we were able to diagnose this problem within a 12-hour span via Summit runs, which prevented several weeks of unproductive trial-and-error DL configuration refinement, and allowed for a more timely convergence on an ultimately viable solution.