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

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At least 271 records · Page 15

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DOE OSTI2023

Deliver Signal Phase and Timing (SPAT) for Energy Optimization of Vehicle Cohort Via Cloud-Computing and LTE Communications

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques. An emulation-based algorithm is applied to predict the traffic signal state changes to provide adequate prediction horizon (e.g., at minimum 2 minutes) for the cohort energy optimization. In fact, the same connectivity and SPAT delivery methodology has been applied to traffic signalized intersections nationwide in the United States upon public agency approvals for access to their firewalled traffic control network and signal control systems or directly to individual controllers. This methodology proves its effectiveness and potential for rapid growth of such SPAT deliveries at mass production scale without needing infrastructure hardware retrofit or excessive communication means. To support the energy optimization of light and heavy-duty vehicle cohorts of mixed automation and propulsion systems (EV, ICE and hybrid), the connection and SPAT deliveries at two sites were completed, including public roads in Washtenaw County, Michigan and closed track test sites at American Center for Mobility (ACM) in Ypsilanti, Michigan. However, only closed test track results at ACM will be presented in this paper. A neuroevolution based optimizer is developed and implemented to control the speed of a vehicle cohort with different propulsion systems and automation levels. Closed track tests showed significant energy savings of the cohort operation.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Modelling feedbacks between human and natural processes in the land system

Abstract. The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human–natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human–natural systems, the following eight lessons were identified that if taken into account by future coupled human–natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

58 GEOSCIENCES↗

DOE OSTI2014

Enabling Detailed Energy Analyses via the Technology Performance Exchange: Preprint

One of the key tenets to increasing adoption of energy efficiency solutions in the built environment is improving confidence in energy performance. Current industry practices make extensive use of predictive modeling, often via the use of sophisticated hourly or sub-hourly energy simulation programs, to account for site-specific parameters (e.g., climate zone, hours of operation, and space type) and arrive at a performance estimate. While such methods are highly precise, they invariably provide less than ideal accuracy due to a lack of high-quality, foundational energy performance input data. The Technology Performance Exchange was constructed to allow the transparent sharing of foundational, product-specific energy performance data, and leverages significant, external engineering efforts and a modular architecture to efficiently identify and codify the minimum information necessary to accurately predict product energy performance. This strongly-typed database resource represents a novel solution to a difficult and established problem. One of the most exciting benefits is the way in which the Technology Performance Exchange's application programming interface has been leveraged to integrate contributed foundational data into the Building Component Library. Via a series of scripts, data is automatically translated and parsed into the Building Component Library in a format that is immediately usable to the energy modeling community. This paper (1) presents a high-level overview of the project drivers and the structure of the Technology Performance Exchange; (2) offers a detailed examination of how technologies are incorporated and translated into powerful energy modeling code snippets; and (3) examines several benefits of this robust workflow.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2014

Gamma Detector Response and Analysis Software - Detector Response Function

GADRAS-DRF uses a Detector Response Function (DRF) to compute the response of gamma-ray detectors incident radiation. The application includes provision for plotting measured and computed spectra and for characterizing detector response parameters based on measurements of a series of calibration sources (e.g., Ba-133, Cs-137, Co-60, and Th-228). An application program interface enables other programs to access the dynamic-link library that is used to compute spectra.

Source record↗

DOE OSTI2016

A Reasoning And Hypothesis-Generation Framework Based On Scalable Graph Analytics

Finding actionable insights from data has always been difficult. As the scale and forms of data increase tremendously, the task of finding value becomes even more challenging. Data scientists at Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g. Urika-XA and Urika-GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with unstructured Big Data. We present the deployment of such a framework called ORiGAMI (Oak Ridge Graph Analytics for Medical Innovations) on the National Library of Medicine s SEMANTIC Medline (archive of medical knowledge since 1994). Medline contains over 70 million knowledge nuggets published in 23.5 million papers in medical literature with thousands more added daily. ORiGAMI is available as an open-science medical hypothesis generation tool - both as a web-service and an application programming interface (API) at http://hypothesis.ornl.gov . Since becoming an online service, ORIGAMI has enabled clinical subject-matter experts to: (i) discover the relationship between beta-blocker treatment and diabetic retinopathy; (ii) hypothesize that xylene is an environmental cancer-causing carcinogen and (iii) aid doctors with diagnosis of challenging cases when rare diseases manifest with common symptoms. In 2015, ORiGAMI was featured in the Historical Clinical Pathological Conference in Baltimore as a demonstration of artificial intelligence to medicine, IEEE/ACM Supercomputing and recognized as a Centennial Showcase Exhibit at the Radiological Society of North America (RSNA) Conference in Chicago. The final paper will describe the workflow built for the Cray Urika-XA and Urika-GD appliances that is able to reason with the knowledge of every published medical paper every time a clinical researcher uses the tool.

graph analytics↗

DOE OSTI2016

Portals Reference Implementation v. 1.0

The Portals reference implementation is based on the Portals 4.X API, published by Sandia National Laboratories as a freely available public document. It is designed to be an implementation of the Portals Networking Application Programming Interface and is used by several other upper layer protocols like SHMEM, GASNet and MPI. It is implemented over existing networks, specifically Ethernet and InfiniBand networks. This implementation provides Portals networks functionality and serves as a software emulation of Portals compliant networking hardware. It can be used to develop software using the Portals API prior to the debut of Portals networking hardware, such as Bull’s BXI interconnect, as well as a substitute for portals hardware on development platforms that do not have Portals compliant hardware. The reference implementation provides new capabilities beyond that of a typical network, namely the ability to have messages matched in hardware in a way compatible with upper layer software such as MPI or SHMEM. It also offers methods of offloading network operations via triggered operations, which can be used to create offloaded collective operations. Specific details on the Portals API can be found at http://portals4.org.

Grant, Ryan E.↗

DOE OSTI2016

Adaptive runtime for a multiprocessing API

A computer-implemented method includes selecting a runtime for executing a program. The runtime includes a first combination of feature implementations, where each feature implementation implements a feature of an application programming interface (API). Execution of the program is monitored, and the execution uses the runtime. Monitor data is generated based on the monitoring. A second combination of feature implementations are selected, by a computer processor, where the selection is based at least in part on the monitor data. The runtime is modified by activating the second combination of feature implementations to replace the first combination of feature implementations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Adaptive runtime for a multiprocessing API

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Home Energy Management System - VOLTTRON Integration

In most Home Energy Management Systems (HEMS) available in the market, different devices running different communication protocols cannot interact with each other and exchange information. As a result of this integration, the information about different devices running different communication protocol can be accessible by other agents and devices running on VOLTTRON platform. The integration process can be used by any HEMS available in the market regardless of the programming language they use. If the existing HEMS provides an Application Programming Interface (API) based on the RESTFul architecture, that API can be used for integration. Our candidate HEMS in this project is home-assistant (Hass). An agent is implemented which can communicate with the Hass API and receives information about the devices loaded on the API. The agent publishes the information it receives on the VOLTTRON message bus so other agents can have access to this information. On the other side, for each type of devices, an agent is implemented such as Climate Agent, Lock Agent, Switch Agent, Light Agent, etc. Each of these agents is subscribed to the messages published on the message bus about their associated devices. These agents can also change the status of the devices by sending appropriate service calls to the API. Other agents and services on the platform can also access this information and coordinate their decision-making process based on this information.

Zandi, Helia↗

DOE OSTI2017

Using Map Service API for Driving Cycle Detection for Wearable GPS Data: Preprint

Following advancements in smartphone and portable global positioning system (GPS) data collection, wearable GPS data have realized extensive use in transportation surveys and studies. The task of detecting driving cycles (driving or car-mode trajectory segments) from wearable GPS data has been the subject of much research. Specifically, distinguishing driving cycles from other motorized trips (such as taking a bus) is the main research problem in this paper. Many mode detection methods only focus on raw GPS speed data while some studies apply additional information, such as geographic information system (GIS) data, to obtain better detection performance. Procuring and maintaining dedicated road GIS data are costly and not trivial, whereas the technical maturity and broad use of map service application program interface (API) queries offers opportunities for mode detection tasks. The proposed driving cycle detection method takes advantage of map service APIs to obtain high-quality car-mode API route information and uses a trajectory segmentation algorithm to find the best-matched API route. The car-mode API route data combined with the actual route information, including the actual mode information, are used to train a logistic regression machine learning model, which estimates car modes and non-car modes with probability rates. The experimental results show promise for the proposed method's ability to detect vehicle mode accurately.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

Commercial Building Energy Saver, API

The CBES API provides Application Programming Interface to a suite of functions to improve energy efficiency of buildings, including building energy benchmarking, preliminary retrofit analysis using a pre-simulation database DEEP, and detailed retrofit analysis using energy modeling with the EnergyPlus simulation engine. The CBES API is used to power the LBNL CBES Web App. It can be adopted by third party developers and vendors into their software tools and platforms.

Hong, Tianzhen↗

DOE OSTI2019

Improving FERRY: Visualization, Refactoring, and Testing

The Frontier Experiment RegistRY System (FERRY) is a metadata database that contains information about employees, the groups and experiments they belong to, and grid mapping and quota management for the Fermi National Accelerator Laboratory. It is predominantly used to acquire user information. FERRY is accessed through the use of APIs (Application Programming Interface), shown in Figure 1. Corresponding attributes are then displayed for the user in JSON (Java Script Object Notation) format. The goal of this project has been to build upon and improve aspects of FERRY. Including the refactoring of the code, building a visual interface, and creating a testing system for FERRY’s APIs.

Segura, Antonio Thomas↗

DOE OSTI2020

REopt Lite Overview & Training Exercise

This training exercise provides users with an introduction to and hands-on, interactive exploration of REopt Lite's capabilities. REopt Lite is a free, publicly available techno-economic optimization web tool for distributed energy systems, developed at the National Renewable Energy Laboratory (NREL). REopt Lite helps organizations evaluate the economic viability of grid-connected solar photovoltaics (PV), wind turbines, and battery storage; identify system sizes and battery dispatch strategies to minimize energy costs; and estimate how long a system can sustain critical load during a grid outage. The model is formulated as a mixed-integer linear program based in an underlying application programming interface (API) that is also free and publicly available. This training activity is structured as a group exercise. Participants split into eight groups and each group is assigned a different hypothetical site to model and assess the opportunity for solar PV + battery storage. Groups work together to develop results for their site and then re-convene to compare and discuss results, inputs/drivers of the analysis, and other factors impacting the decision-making process for behind-the-meter solar PV and battery storage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

NREL's REopt Lite Tool - Open Source

REopt Lite can be accessed via the web tool, application programming interface (API), or open source code. The open source code allows users to add custom features and capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Livewire Data Platform - A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

The Livewire Data Platform is a data storage and exchange platform. It provides: a platform, allowing data sharing and discovery by linking disparate data sources to a single website via application programming interfaces (APIs); a community, building partnerships and collaboration rather than competition; a system, allowing shared data to increase in size and complexity as EEMS evolves.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

DER Planning with Resilience Analysis Using REopt Lite: A Behind-the-Meter Techno-Economic Analysis Tool

REopt Lite is a techno-economic decision support model for behind-the-meter energy systems design and dispatch modeling. REopt Lite is used to optimize energy systems for buildings, campuses, communities, and microgrids. It is based on a Mixed Integer Linear Programming (MILP) optimization model. It is a fully automated and streamlined energy modeling tool that can be used off-the-shelf for a wide variety of distributed generation integration analyses and at the same time is architected to be extensible for user-specific customizations for advanced users and subject matter experts. It is publicly available as a webtool as well as has an Application Programming Interface (API). The API functionality enables programmatic access to the model facilitating smooth integration with other distribution systems modeling tools, and automated multiple scenarios/sensitivity studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Studying Performance Portability of LAMMPS across Diverse GPU-based Platforms

The molecular dynamics simulation software, LAMMPS, utilizes the Kokkos acceleration library to port computation to a diverse set of architectures including those based on GPU accelerators. In addition to Kokkos, LAMMPS contains a vast code base that leverages the CUDA application programming interface using library functions such as cuFFT, CUDA’s fast-fourier transform (FFT) library, and, more recently, also support for AMD’s Heterogeneous Interface for Portability (HIP) that is rapidly growing. While preparing LAMMPS tests for the AMD GPU-based test system precursors to Frontier, we investigated several strategies for accelerating LAMMPS on AMD GPUs, using the AMD Instinct MI100 and MI250X. In this work, we integrated the HIP FFT library, hipFFT, into the particle-particle particle-mesh (PPPM) long-range solver, which allowed the porting of PPPM calculations to the GPUs. Kokkos behavior on the MI100 and MI250X was also investigated through the package kokkos command of LAMMPS, targeting com- munication, memory usage, and particle grid decomposition. The Tersoff, Reax, Lennard-Jones (LJ), EAM, Granular, and PPPM potentials were investigated in this effort, and results from these experiments are provided. The selected potentials were run on Spock (AMD Instinct MI100), Crusher (AMD Instinct MI250X), AFW HPC11 (NVIDIA A100) and Summit (NVIDIA V100), for comparison. Operational roofline models were constructed and analyzed for the Tersoff, Reax, and Lennard-Jones potentials on Crusher and Summit.

Hagerty, Nick↗

DOE OSTI2022

A Tool Kit for Generating Simulated Radiation Measurements for Advanced Reactor Safeguards and Security

A tool kit was developed to simulate and analyze passive radiation measurements of molten salt reactor (MSR) operations to support development of nuclear safeguards approaches for this emerging reactor technology. A Transient Simulation Framework of Reconfigurable Modules (TRANSFORM) multiphysics simulation of an MSR produces time-dependent isotopic inventories at user-selected locations within the model. The tool kit implements the Gamma Detector Response and Analysis Software (GADRAS) application programming interface to inject the TRANSFORM isotopic inventories extracted/processed by a Python pipeline into GADRAS models of user-defined geometries. The TRANSFORM inventories are the source terms used to obtain synthetic measurements from GADRAS-defined detectors. The speed of TRANSFORM and GADRAS simulations enables surveying the large design space of MSRs (e.g., fuel type, fuel salt composition, number of loops) and the plethora of measurements (e.g., location, detector type, and collimation) within the reactor. This has enabled timely assessment of the various measurement locations and detectors to identify the most effective and efficient safeguards approach for a specific MSR design. Lastly, the tool kit also simulates extracted samples that can be aged to a desired dose, enabling stakeholders to optimize a measurement plan to use sample analysis as an element within a broader material accountancy plan.

Westphal, Greg↗