Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Open source software”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Water Security Toolkit User Manual Version 1.2.

The Water Security Toolkit (WST) is a suite of open source software tools that can be used by water utilities to create response strategies to reduce the impact of contamination in a water distribution network . WST includes hydraulic and water quality modeling software , optimizati on methodologies , and visualization tools to identify: (1) sensor locations to detect contamination, (2) locations in the network in which the contamination was introduced, (3) hydrants to remove contaminated water from the distribution system, (4) locations in the network to inject decontamination agents to inactivate, remove, or destroy contaminants, (5) locations in the network to take grab sample s to help identify the source of contamination and (6) valves to close in order to isolate contaminate d areas of the network. This user manual describes the different components of WST , along w ith examples and case studies. License Notice The Water Security Toolkit (WST) v.1.2 Copyright c 2012 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000, there is a non-exclusive license for use of this work by or on behalf of the U.S. government. This software is distributed under the Revised BSD License (see below). In addition, WST leverages a variety of third-party software packages, which have separate licensing policies: Acro Revised BSD License argparse Python Software Foundation License Boost Boost Software License Coopr Revised BSD License Coverage BSD License Distribute Python Software Foundation License / Zope Public License EPANET Public Domain EPANET-ERD Revised BSD License EPANET-MSX GNU Lesser General Public License (LGPL) v.3 gcovr Revised BSD License GRASP AT&T Commercial License for noncommercial use; includes randomsample and sideconstraints executable files LZMA SDK Public Domain nose GNU Lesser General Public License (LGPL) v.2.1 ordereddict MIT License pip MIT License PLY BSD License PyEPANET Revised BSD License Pyro MIT License PyUtilib Revised BSD License PyYAML MIT License runpy2 Python Software Foundation License setuptools Python Software Foundation License / Zope Public License six MIT License TinyXML zlib License unittest2 BSD License Utilib Revised BSD License virtualenv MIT License Vol Common Public License vpykit Revised BSD License Additionally, some precompiled WST binary distributions might bundle other third-party executables files: Coliny Revised BSD License (part of Acro project) Dakota GNU Lesser General Public License (LGPL) v.2.1 PICO Revised BSD License (part of Acro project) i Revised BSD License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of Sandia National Laboratories nor Sandia Corporation nor the names of its con- tributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IM- PLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUD- ING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ii Acknowledgements This work was supported by the U.S. Environmental Protection Agency through its Office of Research and Development (Interagency Agreement # DW8992192801). The material in this document has been subject to technical and policy review by the U.S. EPA, and approved for publication. The views expressed by individual authors, however, are their own, and do not necessarily reflect those of the U.S. Environmental Protection Agency. Mention of trade names, products, or services does not convey official U.S. EPA approval, endorsement, or recommendation. The Water Security Toolkit is an extension of the Threat Ensemble Vulnerability Assessment-Sensor Place- ment Optimization Tool (TEVA-SPOT), which was also developed with funding from the U.S. Environ- mental Protection Agency through its Office of Research and Development (Interagency Agreement # DW8992192801). The authors acknowledge the following individuals for their contributions to the devel- opment of TEVA-SPOT: Jonathan Berry (Sandia National Laboratories), Erik Boman (Sandia National Laboratories), Lee Ann Riesen (Sandia National Laboratories), James Uber (University of Cincinnati), and Jean-Paul Watson (Sandia National Laboratories). iii Acronyms ATUS American Time-Use Survey BLAS Basic linear algebra sub-routines CFU Colony-forming unit CVAR Conditional value at risk CWS Contamination warning system EA Evolutionary algorithm EDS Event detection system EPA U.S. Environmental Protection Agency EC Extent of Contamination ERD EPANET results database file GLPK GNU Linear Programming Kit GRASP Greedy randomized adaptive sampling process HEX Hexadecimal HTML HyperText markup language INP EPANET input file LP Linear program MC Mass consumed MILP Mixed integer linear program MIP Mixed integer program MSX Multi-species extension for EPANET NFD Number of failed detections NS Number of sensors NZD Non-zero demand PD Population dosed PE Population exposed PK Population killed TAI Threat assessment input file TCE Tailed-conditioned expectation TD Time to detection TEC Timed extent of contamination TEVA Threat ensemble vulnerability assessment TSB Tryptic soy broth TSG Threat scenario generation file TSI Threat simulation input file VAR Value at risk VC Volume consumed WST Water Security Toolkit YML YAML configuration file format for WST iv Symbols Notation Definition Example { , } set brackets { 1,2,3 } means a set containing the values 1,2, and 3. [?] is an element of s [?] S means that s is an element of the set S . [?] for all s = 1 [?] s [?] S means that the statement s = 1 is true for all s in set S . P summation P n i =1 s i means s 1 + s 2 + * * * + s n . \ set minus S \ T means the set that contains all those elements of S that are not in set T . %7C given %7C is used to define conditional probability. P ( s %7C t ) means the prob- ability of s occurring given that t occurs. %7C ... %7C cardinality Cardinality of a set is the number of elements of the set. If set S = { 2,4,6 } , then %7C S %7C = 3. v

Klise, Katherine A.↗
DOE OSTI2015

2014 Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Conference Report

The climate and weather data science community met December 9–11, 2014, in Livermore, California, for the fourth annual Earth System Grid Federation (ESGF) and Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Conference, hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UVCDATremain global collaborations committed to developing a new generation of open-source software infrastructure that provides distributed access and analysis to simulated and observed data from the climate and weather communities. The tools and infrastructure created under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change. In addition, the F2F conference fosters a stronger climate and weather data science community and facilitates a stronger federated software infrastructure. The 2014 F2F conference detailed the progress of ESGF, UV-CDAT, and other community efforts over the year and sets new priorities and requirements for existing and impending national and international community projects, such as the Coupled Model Intercomparison Project Phase Six. Specifically discussed at the conference were project capabilities and enhancements needs for data distribution, analysis, visualization, hardware and network infrastructure, standards, and resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Active Learning in the Era of Big Data

Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.

Jamieson, Kevin↗
DOE OSTI2016

Tycho 2: A Proxy Application for Kinetic Transport Sweeps

Tycho 2 is a proxy application that implements discrete ordinates (SN) kinetic transport sweeps on unstructured, 3D, tetrahedral meshes. It has been designed to be small and require minimal dependencies to make collaboration and experimentation as easy as possible. Tycho 2 has been released as open source software. The software is currently in a beta release with plans for a stable release (version 1.0) before the end of the year. The code is parallelized via MPI across spatial cells and OpenMP across angles. Currently, several parallelization algorithms are implemented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Device Scale Modeling of Solvent Absorption using MFIX-TFM

Recent climate change is largely attributed to greenhouse gases (e.g., carbon dioxide, methane) and fossil fuels account for a large majority of global CO 2 emissions. That said, fossil fuels will continue to play a significant role in the generation of power for the foreseeable future. The extent to which CO 2 is emitted needs to be reduced, however, carbon capture and sequestration are also necessary actions to tackle climate change. Different approaches exist for CO 2 capture including both post-combustion and pre-combustion technologies, oxy-fuel combustion and/or chemical looping combustion. The focus of this effort is on post-combustion solvent-absorption technology. To apply CO 2 technologies at commercial scale, the availability and maturity and the potential for scalability of that technology need to be considered. Solvent absorption is a proven technology but not at the scale needed by typical power plant. The scale up and down and design of laboratory and commercial packed bed reactors depends heavily on the specific knowledge of two-phase pressure drop, liquid holdup, the wetting efficiency and mass transfer efficiency as a function of operating conditions. Simple scaling rules often fail to provide proper design. Conventional reactor design modeling approaches will generally characterize complex non-ideal flow and mixing patterns using simplified and/or mechanistic flow assumptions. While there are varying levels of complexity used within these approaches, none of these models resolve the local velocity fields. Consequently, they are unable to account for important design factors such as flow maldistribution and channeling from a fundamental perspective. Ideally design would be aided by development of predictive models based on truer representation of the physical and chemical processes that occur at different scales. Computational fluid dynamic (CFD) models are based on multidimensional flow equations with first principle foundations. CFD models can include a more accurate physical description of flow processes and be modified to include more complex behavior. Wetting performance and spatial liquid distribution inside the absorber are recognized as weak areas of knowledge requiring further investigation. CFD tools offer a possible method to investigating such topics and gaining a better understanding of their influence on reactor performance. This report focuses first on describing a hydrodynamic model for countercurrent gas-liquid flow through a packed column and then on the chemistry, heat and mass transfer specific to CO 2 absorption using monoethanolamine (MEA). The indicated model is implemented in MFIX, a CFD open source software package. The user defined functions needed to build this model are described in detail along with the keywords for the corresponding input file. A test case is outlined along with a few results. The example serves to briefly illustrate the developed CFD tool and its potential capability to investigate solvent absorption.

09 BIOMASS FUELS↗
DOE OSTI2017

Ising Processing Units: Potential and Challenges for Discrete Optimization

The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, presents new opportunities for hybrid-optimization algorithms that leverage these kinds of specialized hardware. In this work, we propose the idea of an Ising processing unit as a computational abstraction for these emerging tools. Challenges involved in using and bench- marking these devices are presented, and open-source software tools are proposed to address some of these challenges. The proposed benchmarking tools and methodology are demonstrated by conducting a baseline study of established solution methods to a D-Wave 2X adiabatic quantum computer, one example of a commercially available Ising processing unit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Automatic optical detection and classification of marine animals around MHK converters using machine vision

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robust principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

National Renewable Energy Laboratory (NREL) Topic 2 Final Report: End-to-End Communication and Control System to Support Clean Energy Technologies

This document is the final report of a two-year development, test, and demonstration project, 'Cohesive Application of Standards- Based Connected Devices to Enable Clean Energy Technologies.' The project was part of the National Renewable Energy Laboratory's (NREL's) Integrated Network Testbed for Energy Grid Research and Technology (INTEGRATE) initiative hosted at Energy Systems Integration Facility (ESIF). This project demonstrated techniques to control distribution grid events using the coordination of traditional distribution grid devices and high-penetration renewable resources and demand response. Using standard communication protocols and semantic standards, the project examined the use cases of high/low distribution voltage, requests for volt-ampere-reactive (VAR) power support, and transactive energy strategies using Volttron. Open source software, written by EPRI to control distributed energy resources (DER) and demand response (DR), was used by an advanced distribution management system (ADMS) to abstract the resources reporting to a collection of capabilities rather than needing to know specific resource types. This architecture allows for scaling both horizontally and vertically. Several new technologies were developed and tested. Messages from the ADMS based on the common information model (CIM) were developed to control the DER and DR management systems. The OpenADR standard was used to help manage grid events by turning loads off and on. Volttron technology was used to simulate a homeowner choosing the price at which to enter the demand response market. Finally, the ADMS used newly developed algorithms to coordinate these resources with a capacitor bank and voltage regulator to respond to grid events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Open and Extensible Control & Analytics Platform for Synchrophasor Data (Final Report)

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project was to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Applied Resiliency for More Trustworthy Grid Operation (ARMORE) (Final Technical Report)

Applied Resiliency for More Trustworthy Grid Operation (ARMORE) is an open-source software system that can perform inspection of network packets and alarm on communication that does not comply with the specified ARMORE policy. ARMORE can be configured to take action to block network traffic based on deep inspection of common substation communications protocols, such as the Distributed Network Protocol (DNP3). After validation for compliance with policy, ARMORE can encapsulate and encrypt legacy communications and resiliently transmit this information among ARMORE nodes (such as between the substation and the control center). Through this peer-based framework for secure information exchange, ARMORE provides the functionality to push secure, fault-tolerant real-time communication capabilities deeper into critical utility networks

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Updated status of the ART neutronic fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Integration Product Line to facilitate the transition from conventional tools to high-fidelity tools. The Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench was initiated in FY-2017. The ARC codes contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC 2 -3 and PERSENT. The ARC integration into the NEAMS Workbench interface relies on the PyARC module which handles the pre- and post-processing of the native ARC codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses. This report describes the ARC capabilities available with the Workbench at the end of FY-2018, and a tutorial is provided together with the automatically-generated code documentation. Integrating the ARC codes into the Workbench benefits directly the Advanced Reactor Technology (ART) Campaign by providing a set of controlled, maintained and validated scripts to generate ARC inputs, which promotes best practices, reduces the learning curve, and facilitates project collaboration. The second benefit from this project is to improve the user experience with the ARC codes: the Workbench interface provides assistance for building an input through auto-completion, real-time validation, access to templates, and visualization. Finally, the ARC integration into the NEAMS Workbench enables new modeling capabilities, those will be extremely useful for advanced reactor design and analyses. The PyARC module facilitates and automatizes complex calculations and workflows for reactor analysis enabling geometrical perturbations, cross-section update through depletion, etc. The Dakota/PyARC coupling in the Workbench was also demonstrated to enable mathematical optimization and sensitivity analysis/uncertainty quantification (SA/UQ) techniques with ARC neutronic simulations. For demonstration purposes, the ARC codes were used through the Workbench for solving the Sodium-cooled Fast Reactor Uncertainty Analysis in Modelling (SFR-UAM) benchmark problems. The ARC codes are currently used at ANL through the Workbench by nuclear engineers for SFR core design analyses. Future efforts will focus on continuously adding modeling capabilities available with the ARC codes, training new users to continue building some experience, and on integrating high-fidelity codes such as PROTEUS into the Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Status of the NEAMS and ARC neutronic fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Integration Product Line to facilitate the transition from conventional tools to high-fidelity tools. The Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench was initiated in FY-2017. The ARC codes contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC2-3, PERSENT and PROTEUS. The ARC integration into the NEAMS Workbench interface relies on the PyARC module which handles the pre- and post-processing of the native ARC codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses. In FY-2019, the effort focused on integrating the explicit assembly management logic of REBUS, the GAMSOR code for gamma heating transport, and of the NODAL solver of PROTEUS. Additional capabilities were also integrated in response to user requests, such as the assembly power peaking calculation and a 2D result plotting capability. For verification and demonstration purposes, the ARC codes were used through the Workbench for solving the Sodium-cooled Fast Reactor Uncertainty Analysis in Modelling (SFR-UAM) benchmark problems, including the newly proposed unit cells and ASTRID problem. Significant effort in FY-2019 focused on training new users from ANL, INL, NCSU, and Westinghouse. In particular, extensive training material was developed in the form of tutorials, including documentation, sample inputs, and associated presentations. The ARC codes are now actively used through the NEAMS Workbench by nuclear engineers at ANL, INL, NCSU, and Westinghouse, for LFR, MSR, micro-reactor, and SFR core design analyses. Future efforts will focus on adding new and existing modeling capabilities available with the ARC and NEAMS codes, training new users and supporting them to continue building user experience.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Multi-scale Molecular Systems Biology: Reconstruction and Model Optimization (Final Report)

Within the Biological and Environmental Research program, the goal of the Genomic Science program is to achieve a predictive, systems-level understanding of plants, microbes, and biological communities to enable biobased solutions to DOE mission challenges in energy and environment. To achieve this goal, an ultimate objective is to develop the knowledgebase, computational infrastructure, and modeling capabilities to advance predictive understanding and manipulation of biological systems. Our project has increased the modeling capabilities and computational infrastructure required to advance predictive understanding and manipulation of biological systems. In particular, we have developed novel algorithms, for modelling biochemical reaction kinetics at genome-scale. These new algorithms have been publicly disseminated as open source software with extensive documentation and tutorials that enable widespread application of this advanced software to practical modelling scenarios. The technical effectiveness of all novel software has been conclusively demonstrated and the quality of this software is maintained by a dedicated continuous integration system. Ultimately, the results of this project will benefit the public because it will enable biologists to more accurately computationally model biological systems that need to be understood to address DOE challenges in energy and environment.

09 BIOMASS FUELS↗
DOE OSTI2019

Variable Precision Computing

This report summarizes the activities and major accomplishments of the Variable Precision Computing Strategic Initiative project. The overarching goal of this project was to initiate and promote a new paradigm in High Performance Computing (HPC) that would fundamentally change how we represent and make use of representations of real numbers in finite precision and that would establish Lawrence Livermore National Laboratory (LLNL) as a leader in precision-related research for HPC. We pursued three integrated and concurrent research thrusts: new, more dynamic data representations to address data motion and capacity limitations; improved mixed precision algorithms to accelerate computation and to leverage new hardware; and new tools to help developers reason about precision and to automate code transformations. Within these thrust areas, we made significant advances in the use of compressed array data types in numerical calculations, in the theoretical justification, in improved performance, and in the prospects of hardware implementation; in the development of metrics to significantly reduce the storage needs of molecular dynamics simulations; in the development and analysis of efficient mixed-precision algorithms for time-dependent partial differential equations and for orthogonal factorization; and in the capability of tools that can analyze sensitivity of computed results to choices in precision and that can make automated code transformations based on such analysis. We established that there are definite opportunities to realize significant improvements in HPC above and beyond the 2x limits of traditional mixed precision using the technologies we have developed. The project produced numerous papers, presentations, and posters in important venues as well as open-source software contributions to the community, and many of the new capabilities have initiated or are being leveraged in ongoing projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Next-Generation Optimization under Uncertainty: Structure-Oriented Algorithms

With the advent of the smart grid, renewable technologies, and carbon emission programs, a key concern is the coordination of national infrastructures such as the electricity, natural gas, and water supply network systems. Anticipating and mitigating uncertainty of weather, demands, and contingencies in a more integrated environment is necessary to maximize resource efficiency and prevent cascading failures that can ultimately lead to catastrophic shortages of supplies. This project developed scalable algorithms for stochastic optimization capable of addressing extreme-scale problems (motivated by challenges in the design and operation of national infrastructures). Specifically, the project developed a new family of algorithms to solve continuous stochastic problems to local and global optimality as well as algorithms to solve mixed-integer convex and nonconvex stochastic programs. We developed supporting local and global convergence theory for these algorithms and implemented the algorithms in open-source software packages that can leverage high-performance computing architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Development and Validation of Predictive Models for In-Cylinder Radiation and Wall Heat Transfer

The lack of accurate submodels for in-cylinder radiation and heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop and design combustion systems for advanced high-efficiency, low-emissions engines. Measurements of wall boundary layers in engines show discrepancies of up to 100% with respect to standard CFD boundary layer models. And analysis of in-cylinder radiation based on the most recent spectral property databases and high-fidelity radiative transfer equation solvers has shown that at operating pressures and exhaust-gas recirculation levels typical of modern compression-ignition truck engines, molecular gas radiation (mainly carbon dioxide and water vapor) can be more important than soot particle radiation, and that a significant fraction of the emitted radiation (50% or more) can be reabsorbed before reaching the walls, thereby acting to redistribute energy in the combustion chamber. In this project, an integrated experimental and simulation approach has been used to generate new physical insight into in-cylinder heat-transfer processes in engines, and to develop computationally practicable CFD-based models that accurately represent the physics. New experimental data have been taken in an optically accessible single-cylinder research engine, and in a multi-cylinder production engine. Those data have provided new insight into the radiative environment in engines. New CFD models have been developed and validated for in-cylinder heat transfer, focusing mainly on radiative heat transfer and coupling between turbulent boundary layer wall heat transfer and radiative heat transfer. The CFD models have been developed and implemented in an open-source software framework that can be shared with other researchers. The models are compatible both with unsteady Reynolds-averaged Navier Stokes (URANS) formulations and with large-eddy simulations (LES) of in-cylinder processes in engines.

02 PETROLEUM↗
DOE OSTI2019

Municipal Portfolio Performance and Policy Opportunities

A wide range of policy tools are in place to enhance energy efficiency in the built environment. However, the lion’s share of today’s energy savings opportunities have to do with energy consumption in existing buildings currently in operation. Many of the policy tools in play, including energy codes, have little to no effect on these existing buildings. New tools and resources are needed to bring existing buildings up to higher levels of energy performance. This project was focused on building a replicable framework, complete with open-source software tools and resources, to empower cities around the country to significantly enhance the energy performance of their own existing buildings and identify opportunities for future improvements. These issues were addressed through the evaluation of the performance of the municipal building stock and policy environments of four mid-size cities: Eugene, Oregon; Providence, Rhode Island; Grand Rapids, Michigan; and Tacoma, Washington. The project team worked closely with these cities to help city staff lead by example and create actionable, implementation-focused strategic energy plans for their own municipal building portfolios and to evaluate and improve city policies. A major focus throughout has been replicability and knowledge transfer (“teaching them to fish” rather than doing the work for the city).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

SIMCCS2.0

SimCCS2.0 is an open-source software package for industry, researchers, and government to design carbon dioxide (CO2) capture, transport, and storage (CCS) infrastructure that optimally links CO2 sources (e.g., power plants) with CO2 sinks (e.g., saline aquifers, depleted oil fields) to reduce industry carbon footprints and increase energy production.

54 ENVIRONMENTAL SCIENCES↗