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This is software developed in the course of my dissertation work, which was funded by Sandia. The software includes a library (the Streaming Analytics Machine or SAM) for expressing machine learning and subgraph matching over streaming data sources. It also includes a utility that will convert from a high-level language, the Streaming Analytics Language (SAL) to SAM. SAND2019-4322 M
The inviscid performance of an inward turning inlet design is calculated computationally for the first time. Hypersonic vehicle designs based on the inward turning inlets have been shown analytically to have increased effective specific impulse and lower heat load than comparably designed vehicles with two-dimensional inlets. The inward turning inlets are designed inversely from inviscid stream surfaces of known flow fields. The computational study is performed on a Mach 12 inlet design to validate the performance predicted by the design code (HAVDAC) and calculate its off-design Mach number performance. The three-dimensional Euler equations are solved for Mach 4, 8, and 12 using a software package called SAM, which consists of an unstructured mesh generator (SAMmesh), a three-dimensional unstructured mesh flow solver (SAMcfd), and a CAD-based software (SAMcad). The computed momentum averaged inlet throat pressure is within 6% of the design inlet throat pressure. The mass-flux at the inlet throat is also within 7 % of the value predicted by the design code thereby validating the accuracy of the design code. The off-design Mach number results show that flow spillage is minimal, and the variation in the mass capture ratio with Mach number is comparable to an ideal 2-D inlet. The results from the inviscid flow calculations of a Mach 12 inward turning inlet indicate that the inlet design has very good on and off-design performance which makes it a promising design candidate for future air-breathing hypersonic vehicles.
The System Advisor Model (SAM) is a mature suite of techno-economic models for many renewable energy technologies that can be downloaded for free as a desktop application or software development kit. SAM is used for system-level modeling, including generating performance pro the release of the code as an open source project on GitHub. Other additions that will be covered include the ability to download data directly into SAM from the National Solar Radiation Database (NSRDB) and up- dates to a user-interface macro that assists with PV system sizing. A brief update on SAM's battery model and its integration with the detailed photovoltaic model will also be discussed. Finally, an outline of planned work for the next year will be presented, including the addition of a bifacial model, support for multiple MPPT inputs for detailed inverter modeling, and the addition of a model for inverter thermal behavior.
The System Advisor Model (SAM) is free software developed by the National Renewable Energy Laboratory (NREL) for predicting the performance of renewable energy systems and analyzing the financial feasibility of residential, commercial, and utility-scale grid-connected projects. SAM offers several options for predicting the performance of photovoltaic (PV) systems. The model requires that the analyst choose from three PV system models, and depending on that choice, possibly choose from three module and two inverter component models. To obtain meaningful results from SAM, the analyst must be aware of the differences between the model options and their applicability to different modeling scenarios. This paper presents an overview the different PV model options and presents a comparison of results for a 200-kW system using different model options.
The work performed in this CRADA resulted in significant progress toward the development of a Thermal-fluid test-stand based on NEAMS tools. Significant work has been achieved in this area with simulations performed in Nek5000 of the heat and fluid flow in twisted tube heat exchangers and various software and modeling improvements in SAM geared toward heat exchanger simulations. In particular a set of simulations of flow and heat transfer in twisted elliptical tube geometries has been performed with Nek5000. The method was validated by simulating a case at a moderate Reynolds number and relatively high Froude number. This case was demonstrated to predict a Nusselt number in excellent agreement with the applicable correlation found in literature. It was further shown that at lower Froude numbers, this agreement becomes much worse. Additional cases were then simulated with low Froude numbers for both a square and a triangular unit cell to test the effect of pitch-to-maximum diameter ratio for the purposes of future CFD modeling. The results have proven invaluable to understand the flow physics in twisted tubes and provide reference data for design. Results have been summarized in a conference article. Moreover, work in SAM has led to significant improvement of software quality, the creation of a set of benchmarks for natural circulation and other significant software improvement.
A differential phase scanning acoustic microscope (DP-SAM) was developed, fabricated, and tested in this project. This includes the acoustic lens and transducers, driving and receiving electronics, scanning stage, scanning software, and display software. This DP-SAM can produce mechanically raster-scanned acoustic microscopic images of differential phase, differential amplitude, or amplitude of the time gated returned echoes of the samples. The differential phase and differential amplitude images provide better image contrast over the conventional amplitude images. A specially designed miniature dual beam lens was used to form two foci to obtain the differential phase and amplitude information of the echoes. High image resolution (1 micron) was achieved by applying high frequency (around 1 GHz) acoustic signals to the samples and placing two foci close to each other (1 micron). Tone burst was used in this system to obtain a good estimation of the phase differences between echoes from the two adjacent foci. The system can also be used to extract the V(z) acoustic signature. Since two acoustic beams and four receiving modes are available, there are 12 possible combinations to produce an image or a V(z) scan. This provides a unique feature of this system that none of the existing acoustic microscopic systems can provide for the micro-nondestructive evaluation applications. The entire system, including the lens, electronics, and scanning control software, has made a competitive industrial product for nondestructive material inspection and evaluation and has attracted interest from existing acoustic microscope manufacturers.
The System Advisor Model (SAM) is a free software tool that performs detailed analysis of both system performance and system financing for a variety of renewable energy technologies. This report provides detailed validation of the SAM flat plate photovoltaic performance model by comparing SAM-modeled PV system generation data to actual measured production data for nine PV systems ranging from 75 kW to greater than 25 MW in size. The results show strong agreement between SAM predictions and field data, with annualized prediction error below 3% for all fixed tilt cases and below 8% for all one axis tracked cases. The analysis concludes that snow cover and system outages are the primary sources of disagreement, and other deviations resulting from seasonal biases in the irradiation models and one axis tracking issues are discussed in detail.
The System Advisor Model (SAM) is a free software that enables detailed performance and financial analysis for energy systems. • Conducts technoeconomic analysis of energy technologies to facilitate planning and decision making.
The System Analysis Module (SAM), developed at Argonne National Laboratory and by collaborators at other organizations, is for advanced non–light water reactor safety analysis. SAM aims to provide fast-running, modest-fidelity, whole-plant transient analysis capabilities that are essential for fast-turnaround design scoping and engineering analyses of advanced reactor concepts. To facilitate code development, SAM utilizes the MOOSE object-oriented application framework, its underlying finite element library, and linear and nonlinear solvers to leverage modern advanced software environments and numerical methods. SAM aims to solve tightly coupled physical phenomena, including fission reaction, heat transfer, fluid dynamics, and thermal-mechanical responses in advanced reactor structures, systems, and components with high accuracy and efficiency. Finally, this paper gives an overview of the SAM code development, including goals and functional requirements, physical models, current capabilities, verification and validation, software quality assurance, and examples of simulations for advanced nuclear reactor applications.
In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.
As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.
This project aims to raise the SAM code's technical and commercial maturity level to enable the Kairos Power ("Kairos") to use SAM to support its KP-FHR design analysis and licensing application. Argonne National Laboratory ("Argonne") has actively developed and maintained SAM, a modern system-level analysis tool for advanced nonlight water reactors safety analysis. Kairos is currently actively pursuing development of an FHR design and associated technology, and consequently requires a pedigreed safety analysis tool. The purpose of this project is to increase the maturity of the SAM code for the modeling and simulation of the KP-FHR design, thus enabling its use in safety analyses that support licensing application. Argonne will primarily be responsible for software design, development, and testing; while Kairos will be responsible for software requirements, assessment of software capabilities, needs, gaps, and priorities, and development of proprietary models. The research and development activities for the joint SAM development project include: a series of identification and prioritization studies on design characteristics, event sequences, relevant phenomena, and software capabilities; SAM capability enhancements for specific KP-FHR systems and components; performing code verification and validations; integrating uncertainty quantification (UQ), model calibration, and sensitivity analysis (SA) techniques in safety analyses; and raising the software quality rigor level for commercial-grade applications.
During operations, NOvA produces between 5,000 and 7,000 raw files per day with peaks in excess of 12,000. These files must be processed in several stages to produce fully calibrated and reconstructed analysis files. In addition, many simulated neutrino interactions must be produced and processed through the same stages as data. To accommodate the large volume of data and Monte Carlo, production must be possible both on the Fermilab grid and on off-site farms, such as the ones accessible through the Open Science Grid. To handle the challenge of cataloging these files and to facilitate their off-line processing, we have adopted the SAM system developed at Fermilab. SAM indexes files according to metadata, keeps track of each file's physical locations, provides dataset management facilities, and facilitates data transfer to off-site grids. To integrate SAM with Fermilab's art software framework and the NOvA production workflow, we have developed methods to embed metadata into our configuration files, art files, and standalone ROOT files. A module in the art framework propagates the embedded information from configuration files into art files, and from input art files to output art files, allowing us to maintain a complete processing history within our files. Embedding metadata in configuration files also allows configuration files indexed in SAM to be used as inputs to Monte Carlo production jobs. Further, SAM keeps track of the input files used to create each output file. Parentage information enables the construction of self-draining datasets which have become the primary production paradigm used at NOvA. In this study we will present an overview of SAM at NOvA and how it has transformed the file production framework used by the experiment.
While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.
The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM development aims for advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability for reactor transient analyses. To facilitate the code development, SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SAM focuses on modeling advanced reactor concepts such as SFRs (sodium fast reactors), LFRs (lead-cooled fast reactors), and FHRs (fluoride-salt-cooled high temperature reactors) or MSRs (molten salt reactors). These advanced concepts are distinguished from light-water reactors in their use of single-phase, low-pressure, high-temperature, and low Prandtl number (sodium and lead) coolants. As a new code development, the initial effort has been focused on modeling and simulation capabilities of heat transfer and single-phase fluid dynamics responses in Sodium-cooled Fast Reactor (SFR) systems. The system-level simulation capabilities of fluid flow and heat transfer in general engineering systems and typical SFRs have been verified and validated. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As the code is still under ongoing development, this SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.
The CSP Systems Analysis project was a three-year effort supporting the Concentrating Solar Power (CSP) Subprogram within the Solar Energy Technologies Office of the U.S. Department of Energy (DOE). The goal of the CSP Systems Analysis project was to provide timely and accurate CSP cost data to the DOE and predict performance and cost for emerging technologies that may impact research directions and industry investment. The project consisted of six, mostly independent tasks. Major accomplishments over the three-year period of performance were as follows. The NREL team maintained current cost estimates for CSP technologies by annual updates to the cost input parameters within NREL's System Advisor Model (SAM). SAM is a performance and cost simulation software that includes technology models for the primary CSP technologies. During the period from 2016 to 2018, the estimated cost within SAM's default CSP molten-salt power tower technology dropped from 13.0 to 11.1 cent/kWh (real dollars without incentives). Power cycle models for the supercritical carbon dioxide (sCO2) Brayton Cycle were developed and made an option within SAM's molten-salt power tower model. These models were subsequently used to evaluate the cost reduction potential of alternative salts. The partial-cooling model was found to provide the greatest cost-reduction potential due to its combination of efficiency and temperature differential across the turbine and thermal energy storage (TES) system. These studies were documented in two journal articles. NREL's optical modeling software SolTrace and SolarPILOT were made more versatile and released as open-source software to the CSP community. These tools help researchers and developers to model and optimize the optical performance of CSP collector systems. The new features were highlighted in a recorded webinar that can be accessed from the NREL SAM website. New models for solar-thermal systems, that is, applications for solar industrial process heat, were developed, validated, and installed within SAM. The analysis includes a 2018 review of linear collectors in the market that are tailored for solar process heat applications. In 2018 the NREL team also developed an annual simulation for a direct steam generation system integrated with a latent-heat TES system. This analysis was submitted for journal publication. The NREL team continued to support the exchange of information and development of CSP guidelines within the international CSP community of SolarPACES. Much of the work under this project was presented at SolarPACES, including the development of a modeling checklist to help CSP stakeholders standardize the models used for estimating CSP performance and cost. The CSP Systems Analysis project also supported DOE requests for tracking and reporting programmatic targets for the CSP Subprogram.
This report documents the Verification and Validation (V&V) Plan for software verification and validation of the SFR System Analysis Module (SAM), developed at Argonne National Laboratory for sodium fast reactor whole-plant transient analysis. SAM is developed under the DOE NEAMS program and is part of the Reactor Product Line toolkit. The SAM code, the phenomena and computational models of interest, the software quality assurance, and the verification and validation requirements and plans are discussed in this report.
This software consists of a Plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool under development at Argonne National Laboratory.