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DOE OSTI2023

Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning

Recent years have seen a rich literature of data-driven approaches designed for power grid applications. However, insufficient consideration of domain knowledge can impose a high risk to the practicality of the methods. Specifically, ignoring the grid-specific spatiotemporal patterns (in load, generation, and topology, etc.) can lead to outputting infeasible, unrealizable, or completely meaningless predictions on new inputs. To address this concern, this paper investigates real-world operational data to provide insights into power grid behavioral patterns, including the time-varying topology, load, and generation, as well as the spatial differences (in peak hours, diverse styles) between individual loads and generations. Then based on these observations, we evaluate the generalization risks in some existing ML works caused by ignoring these grid-specific patterns in model design and training.

Li, Shimiao↗

DOE OSTI2023

QASMTrans: A QASM Quantum Transpiler Framework for NISQ Devices

In quantum computing, transpilation plays a crucial role in converting high-level, machine-independent quantum circuits into circuits specially for a quantum device, considering factors such as basis gate set, topology, error profile, etc. Yet, the efficiency of transpilation remains a significant bottleneck, particularly when dealing with very large QASM level input files. In this paper, we present QASMTrans, a C++ based high-performance quantum transpiler framework that can demonstrate on average 50-100× speedups compared to the internal transpiler of Qiskit. Particularly, for large dense circuits such as ’uccsd n24’ and ’qft n320’ incorporating millions of gates, QASMTrans can successfully transpile in 69s and 31s, respectively, while Qiskit failed to finish in one hour. Using QASMTrans as the baseline, it becomes more feasible to explore much larger design space and impose more comprehensive compiler optimizations.

Hua, Fei↗

DOE OSTI2025

Development of Emergency Vehicle Preemption Strategies on Smart Corridors in a Digital Twin Environment

Emergency Response Vehicles (ERVs), such as firetrucks, ambulances, etc. operate with the purpose of saving lives and mitigating property damage. As such, ERV travel-time reductions may result in significant benefits to the community. A common strategy to improve travel times is Emergency Vehicle Preemption (EVP). EVP seeks to reduce ERV delays by providing the right-of-way to ERVs as they approach an intersection. This study proposes a new Dynamic Preemption strategy that determines the need for preemption prior to the ERV reaching the vicinity of the intersection, utilizing real-time data streams. This paper evaluates the effectiveness of some existing and proposed preempt control strategies using a digital twin testbed consisting of a series of signalized intersections on an urban arterial in Georgia. The best EVP strategy maximizes the improvement in ERV travel time while minimizing the adverse effect of preemption on the traffic in conflicting directions. Therefore, this study evaluates both the positive impact of EVP on the ERV as well as the adverse impact on the cross-street traffic. The study found that the potential exists for significant improvements in ERV travel time with the proposed Dynamic Preemption strategy, with minimal impact to the conflicting traffic. For the simulation corridor there was a 20% reduction in the ERV travel times with the implementation of the Dynamic Preemption strategy, compared to traditional EVP practices.

Roy, Somdut [Georgia Institute of Technology]↗

DOE OSTI2024

Studying CPU and memory utilization of applications on Fujitsu A64FX and Nvidia Grace Superchip

ARM-based manycore CPU architectures are well-positioned to provide the rising memory throughput requirements of modern data intensive scientific applications in High Performance Computing (HPC). The Fujitsu A64FX CPU platform is based on the ARM v8.2A architecture, and is the processor of the flagship Japanese supercomputer - "Fugaku", which was previously ranked as the #1 supercomputer in the world according to the Top500 list. The Nvidia Grace superchip features 144 Neoverse V2 cores based on the ARMv9 architecture with 4x128b SVE2, providing exceptional computational power. The chip supports up to 480GB of memory, making it ideal for AI, machine learning, and scientific computing workloads. In this paper, we conduct a thorough performance exploration of a variety of parallel bandwidth-sensitive benchmarks and applications compiled with the native Fujitsu compiler on a Fugaku A64FX compute node and ARM (LLVM) Compiler on an NVIDIA Grace superchip compute node, engaging all the computational cores per cluster using OpenMP multithreading (assuming the cores can drive the available bandwidth). Our ultimate goals are to study the resource utilization of scientific applications and benchmarks on A64FX and Grace superchip, considering graph application scenarios ( GAP Benchmark suite) and eleven appli- cation proxies from the Rodinia heterogeneous benchmark suite (considering domains such as Data Mining, Bioinformatics, Fluid Dynamics, Pattern Recognition, etc.). Through exhaustive performance monitoring, we quantify the resource utilization of diverse OpenMP-based HPC applications on both the Fujitsu A64FX and the Nvidia Grace Superchip platforms.

benchmarking, Performance Analysis, High performan↗

DOE OSTI2024

Photon Upconversion at Organic-Inorganic Interfaces

Photon upconversion is a process that combines low-energy photons to form useful high-energy photons. There are potential applications in photovoltaics, photocatalysis, biological imaging, etc. Semiconductor quantum dots (QDs) are promising for the absorption of these low-energy photons due to the high extinction coefficient of QDs, especially in the near infrared (NIR). This allows the intriguing use of diffuse light sources such as solar irradiation. In this review, we describe the development of this organic-QD upconversion platform based on triplet-triplet annihilation, focusing on the dark exciton in QDs with triplet character. Then we introduce the underlying energy transfer steps, starting from QD triplet photosensitization, triplet exciton transport, triplet-triplet annihilation, and ending with the upconverted emission. Design principles to improve the total upconversion efficiency are presented. We end with limitations in current reports and proposed future directions. This review provides a guide for designing efficient organic-QD upconversion platforms for future applications, including overcoming the Shockley-Queisser limit for more efficient solar energy conversion, NIR-based phototherapy, and diagnostics in vivo.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Effects of Ink Formulation on the Structure and Performance of PGM-Free Catalyst Layer in PEMFCs

Platinum group metal (PGM) catalysts are the major electrocatalysts for oxygen reduction reaction (ORR) in the polymer electrolyte membrane fuel cells (PEMFCs). The cost becomes unaffordable if the PEMFC is in massive application. The PGM-Free catalyst shows very promising activity in rotation disk electrode (RDE) testing. The half-wave potential could reach 0.91 V versus standard hydrogen electrode (SHE). However, in a membrane electrode assembly (MEA), the performance of PGM-Free catalysts is not good enough to replace the PGM catalysts. Since the PGM-free catalysts are so different from the PGM catalysts in terms of catalytic activity, stability, surface conditions, particle size, etc., the fabrication of PGM-Free catalyst MEA cannot simply copy the method of making PGM MEA. Here we proposed a novel method of fabricating PGM-Free catalyst MEA, so that the intrinsic catalyst activity from RDE can be translated into MEA performance. The method is based on the catalyst coated membrane (CCM) method using optimized ionomer to carbon (I/C) ratio and solvent mixture of catalyst ink. Using this method, the PGM-free catalyst MEA achieved the current density 44.9 mA cm -2 at 0.9 V iR-free in H 2 /O 2 and 150 mA cm -2 at 0.8 V in H 2 /air, which surpassed the performance targets of US Department of Energy (DOE)for PGM-Free catalyst MEA. The property (solvent composition, dispersion of catalyst and ionomer in an ink), structure (pore structure) and the MEA performance have been characterized using, mercury intrusion porosimetry (MIP), MEA testing. A property-structure-performance relationship has been established.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Editors’ Choice—Perspective—Challenges in Moving to Multiscale Battery Models: Where Electrochemistry Meets and Demands More from Math

There has been significant recent interest in studying multiscale characteristics of current and next-generation batteries, including lithium-metal and lithium-sulfur batteries. Advances in computing power make researchers believe that the detailed multiscale models can be efficiently simulated to arrive at the insights for the degradation and performance loss; however, this is not true and special attention needs to be paid to local singularities, boundary layers, moving boundaries, etc. This article presents 2D examples that illustrate the importance of grid convergence studies, provides well-defined detailed models to test the efficiency of numerical schemes, and discusses the associated simulation challenges.

Shah, Krishna (ORCID:0000000278026361)↗

DOE OSTI2022

Intermediate-Temperature Proton Exchange Membranes Based on Cerium Ultraphosphate Composited with Polybenzimidazole

This paper reports the rational fabrication and structural, thermal, mechanical and electrochemical characterization of a new type of intermediate-temperature (IT) polymer-inorganic composite (PIC) proton exchange membranes (PEMs) that are made of cerium ultraphosphate (CeP 5 O 14 —CUP) as the solid-state proton conductor composited with a high-temperature (HT) polybenzimidazole (PBI) as the polymeric binder. Here, flexible PBI-CUP PIC membranes with the thickness of ~135 μ m and CUP mass fraction of up to 75% were prepared by solution-casting without additional acid-doping (e.g., phosphoric acid). The proton conductivity of the fabricated IT-PIC-PEMs was up to 5.80 × 10 –2 S cm –1 as measured from a prototype IT PEM fuel cell (PEMFC) operated at 200 °C in the humidified hydrogen and air environment. This type of IT-PIC-PEMs also demonstrated sufficient mechanical strength and flexibility, excellent thermal stability (up to 350 °C), and very good durability of the proton conductivity (within the test duration of 500 h). The present experimental study shows the promising future of the IT-PIC-PEMs for applications in various IT electrochemical processes including IT-PEMFCs, IT-electrolyzers, etc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Anolyte Enhances Catalyst Utilization and Ion Transport Inside a CO 2 Electrolyzer Cathode

Electrochemical CO 2 reduction is a promising technology to capture and convert CO 2 to valuable chemicals. High Faradaic efficiencies of CO 2 reduction products are achieved with zero-gap alkaline CO 2 electrolyzers with a supporting electrolyte at the anode (anolyte). Herein, we investigate the effect of anolyte on the electrode properties such as catalyst utilization, ionic accessibility etc. of a CO 2 reduction cathode using electrochemical techniques and cell configurations that avoid the complexities related to co-electrolysis. Using 1M KOH as the anolyte and a Cu gas-diffusion-electrode with low Nafion content as the model CO 2 reduction electrode, we find that electrode capacitance (proxy for electrochemically active surface area) and ionic conductivity inside the cathode increase approximately 4 and 447 times, respectively, in presence of KOH. Liquid anolyte wets the electrode’s pore structure more efficiently than capillary condensation of feed water vapor. The ionomer coverage is very low, and its distribution inside the electrode is highly fragmented. Surface ion conduction mechanisms inside the electrode are orders of magnitude lower than the bulk ion conduction in presence of anolyte. This study shows that when an anolyte (e.g., KOH) is used, catalyst utilization and ionic accessibility inside the electrode increase significantly.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Improving the Long-term Cycle Performance of xLi 2 MnO 3 ·(1-x)LiMeO 2 /Li 4 Ti 5 O 12 Cells via Prelithiation and Electrolyte Engineering

Toward the development of high energy density and long lifetime batteries for behind-the-meter storage (BTMS) applications, Li- and Mn-rich layered oxide cathode (xLi 2 MnO 3 ·(1-x)LiMeO 2 , Me = Ni, Mn, and etc., LMR-NM) and Li 4 Ti 5 O 12 (LTO) anode system was examined. To mitigate the major degradation mechanisms at each electrode (i.e., loss of Li inventory (LLI) at the anode and transition metal dissolution and oxygen release at the cathode), two approaches were taken—prelithiating the LTO electrode and varying the electrolyte solvent compositions. The effect of prelithiation and electrolyte engineering on the long-term cycle performance of LMR-NM/LTO cells were systematically evaluated via electrochemical analyses and post-mortem characterizations. By using a prelithiated LTO anode and supplying additional Li to the system, the capacity retention of LMR-NM/LTO system was improved. The degree of enhancement was dependent on the types of electrolytes used, as their decomposition products determined the level of LLI. With increased capacity retention, however, the cathode was utilized to a greater extent, resulting in more severe loss of the cathode active material. Thus, all degradation mechanisms should be considered comprehensively when designing high performance LMR-NM/LTO cells to account for their complex interplay.

25 ENERGY STORAGE↗

DOE OSTI2022

Multi-Scale Modeling of Hydrogen Transport in a Porous Fuel Cell Anode

Proton-exchange-membrane fuel cells (PEMFC) are a clean energy conversion alternative to traditional fossil-fuel combustion; however, transport resistances in the electrode pose a lower-limit to catalyst loading and commercialization of PEMFCs. PEMFCs consist of simultaneous hydrogen (H 2 ) oxidation and oxygen (O 2 ) reduction at the anode and cathode, respectively. Here, while oxygen transport resistances in PEMFCs have been widely studied both experimentally and analytically, hydrogen transport resistances are less understood. Herein, we present a physics-based model that encompasses multi-scale transport within the anode side of the PEMFC. The O 2 in the cathode here is omitted and replaced with H 2 to deconvolute O 2 transport resistance contributions, similar to that of a hydrogen pump. Replication of the hydrogen pump setup allows for comparison of the model against experimental analysis of H 2 gas-transport resistance in H 2 limiting-current experiments, which can also inform gas transport (including oxygen) in general. Herein, we present a multi-scale analytical model of the porous anode catalyst layers and individual catalyst agglomerates that enables determination of the effects of electrode morphology such as agglomerate size, catalyst loading, etc. on H 2 transport resistance through the porous electrode to complement and better understand H 2 limiting current experiments and deconvolute local H 2 transport resistances.

Zhang, Rosa↗

DOE OSTI2023

(Invited) Fuel Cell Component Durability for Million Mile Fuel Cell Trucks

While significant advances have been made and early commercial fuel cell light-duty vehicles (LDVs) are starting to be produced, fuel cells in the heavy-duty-vehicle (HDV) transportation sector (including trucks, long-haul semitrailers, maritime, trains, etc.) are nascent, despite the fact that advantages of fuel cells compared to both diesel and electric powertrains are very compelling in terms of emissions, charging time, efficiency, power-to-weight ratio, among others. However, the fuel-cell technology for HDVs requires a paradigm shift in fuel-cell research and development compared to LDVs, where the emphasis becomes efficiency and improvements in durability instead of a focus on increased power densities and lower cell costs. Heavy-duty applications require significantly longer vehicle lifetimes (>25,000 hours/1,000,000 miles for heavy-duty trucks), and therefore require improved fuel cell durability compared to light-duty vehicles. In 2020, HFTO formed the Million Mile Fuel Cell Truck Consortium (M2FCT) that includes a core team of five national laboratories to overcome durability and efficiency challenges in PEMFCs for heavy-duty applications with an initial focus on long-haul trucks. While targets and testing protocols have been developed for light-duty vehicles, the same level of targets and testing protocols have not been established for heavy-duty transportation. With operational times of greater than > 25,000 hours required, the need for well-developed accelerated stress tests (ASTs) is amplified. Results from these ASTs demonstrate the need for more durable electrode layers and well-controlled potential variations. Finally, this presentation will provide an overview of the DOE's Fuel Cell R&D approach, highlighting past and current activities, as well as strategies to enable fuel cell competiveness for heavy-duty applications.

25 ENERGY STORAGE↗

DOE OSTI2022

ROS-Ethereum: A Convenient Tool to Bridge ROS and Blockchain (Ethereum)

Robot Operating System (ROS) has received widespread utilization with the development of robotics, self-driving, etc., recently. Meanwhile, the other technology blockchain is frequently applied to various fields with its trustworthy characteristics and immutability in data storage. However, ROS has no ability to interact with the blockchain, which hinders research in related fields. Therefore, we wonder if we can develop a convenient tool to bridge ROS and blockchain. Inspired by this, we propose ROS-Ethereum. It bridges ROS and Ethereum, a widely used blockchain platform. ROS-Ethereum is based on the User Datagram Protocol (UDP) communication mechanism and the SM algorithm family along with Ethereum technology. Simply put, ROS-Ethereum allows users to invoke the contract when interacting with the blockchain, which makes this process easier and safer. We conduct experiments in real robots to verify the effectiveness of ROS-Ethereum and evaluate it from the following metrics: (1) the encryption efficiency and stability of the algorithm and (2) ROS-Ethereum transaction response time and packet loss rate.

Zhang, Shenhui↗

DOE OSTI2026

Pioneer WEC v1 Ocean Deployment

There are seven zip files of data pertaining to the Pioneer WEC v1 ocean deployment.(1-6) Pioneer multiple sensor data "Month Year".zip: contains monthly data from the majority of onboard instruments (e.g., electrical power, mechanical motion, etc.)(7) Pioneer vibration sensor data full 6 months.zip: contains data from the vibration sensor instrument for the full 6 month deployment

Ocean sensing↗

DOE OSTI2020

Counting Occupants Using Network Technology (COUNT) v0.1

With this COUNT software, we can run a simple query on a campus's Wireless Local Area Network controller (WLAN controller) to obtain the number of connected devices per access point across the whole campus and this can be used as a proxy for the actual number of occupants in the campus. The software supports user defined functions to parse access point names to retrieve more information (e.g.: building names, room numbers etc.) and also allows post-processing of the data.

Prakash, AnandKrishnan↗

DOE OSTI2020

UnitTesterSG

UnitTesterSG is a unit testing framework that is designed for nested and/or scientific/engineering data structures. It is designed primarily for testing the outputs if a single function or simulation run by storing the expected results file such that comparisons to the stored output can be made with unit tests after the function or software has been edited. This module is designed to be able to unit test arrays, strings, as well as nested and deeply nested objects (including arrays with tuples inside, arrays with strings inside, etc.). The module is compatable with nested objects, and thus has a dependency on the nestedObjectsFunctions module within. The module takes *calculated* results and then compares them to *expected* results. If no expected results are available (or they do not match the calculated results) the module then offers to store the calculated results as expected results for next time.

Savara, Aditya [Oak Ridge National Lab. (ORNL), Oa↗

DOE OSTI2020

TEAL

TEAL is a financial performance calculator plugin for the RAVEN code, framework, resolving around the computation of Net Present Value and associated financial metrics. TEAL can make use of inflation rates, taxation, escalation factors, capital expenditure economy of scale scaling factors. The unique feature of TEAL is the capability to be linked with RAVEN external models and build corresponding cash flows using the variables computed by those external models. In addition to be able to use the capability to generate cash flows derived from complex physical models generated by RAVEN, another distinctive feature of TEAL is the capability to provide financial risk/probabilistic metrics that can empower RAVEN to perform optimization/analysis driven by financial risk augmentations. Optimization, robust optimization, parametric studies, large parallel simulations, sensitivity analysis, data mining, etc. are just some of the capabilities that can be leveraged.

Alfonsi, Andrea↗

DOE OSTI2020

TripleGraph

RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).

Sangkeun, MattLee↗