Results for “concurrent design” — Page 2

DOE OSTI2024

Warm Unit Stand Assembly and Testing for Proton Improvement Plan - II

The Proton Improvement Project II (PIP II), situated at Fermilab, signifies a critical advancement in the realm of high-energy physics. PIP II, a linear accelerator renovation endeavor, aspires to double the output of the existing proton beam, reinforcing Fermilab’ s position as a vanguard in this field. The proton beam's creation involves a series of high-frequency cryomodules, necessitating environmental temperature arrays of magnets and vacuum pumps henceforth described as ‘Warm Units.’ The Warm Units include design features of : 1. insertion between the cryomodules, 2. multi-stage adjustments in six degrees of freedom to ensure precise beam alignment; 3. Natural frequency modes that avoid specified ranges. In adherence to Fermilab’ s stringent safety standards, comprehensive testing procedures are slated to validate the Warm Units' capacity to simultaneously achieve local alignment adjustments while averting low-frequency oscillation less than 15 Hertz. The testing regimen will scrutinize the Warm Units' alignment adjustment capabilities and their resilience against low-frequency oscillations, with an overarching objective of satisfying the Final Design Review criteria specific to the PIP II initiative. This project works to furnish technicians responsible for the assembly of Warm Units with a comprehensive guide for successful installation, concurrently documenting any requisite design modifications essential for achieving a real-world configuration.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials

The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning and operation. The SNN architecture explores novel neuromorphic devices that are based on resistive-switching materials, such as memristors and electrochemical RAM. Equally important, Abisko uses a deep codesign approach to pursue this goal by engaging experts from across the entire range of disciplines: materials, devices and circuits, architectures and integration, software, and algorithms. Here, the key objectives of our Abisko project are threefold. First, we are designing an energy-optimized high-performance neuromorphic accelerator based on SNNs. This architecture is being designed as a chiplet that can be deployed in contemporary computer architectures and we are investigating novel neuromorphic materials to improve its design. Second, we are concurrently developing a productive software stack for the neuromorphic accelerator that will also be portable to other architectures, such as field-programmable gate arrays and GPUs. Third, we are creating a new deep codesign methodology and framework for developing clear interfaces, requirements, and metrics between each level of abstraction to enable the system design to be explored and implemented interchangeably with execution, measurement, a model, or simulation. As a motivating application for this codesign effort, we target the use of SNNs for an analog event detector for a high-energy physics sensor.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Donor End-Capped Alkyl Chain Length Dependent Non-Radiative Energy Loss in All-Small-Molecule Organic Solar Cells

A critical bottleneck for further efficiency breakthroughs in organic solar cells (OSCs) is to minimize the non-radiative energy loss (eΔV nr ) while maximizing the charge generation. With the development of highly emissive low-bandgap non-fullerene acceptors, the design of high-performance donors becomes critical to enable the blend with the electroluminescence quantum efficiency to approach or surpass the pristine acceptor. Herein, by shortening the end-capped alkyl chains of the small-molecular donors from hexyl (MPhS-C6) to ethyl (MPhS-C2), the material obtained aggregation that was insensitive to thermal annealing (TA) along with condensed packing simultaneously. The former leads to small phase separation and suppressed upshifts of the highest occupied molecular orbital energy level during TA, and the latter facilitates its efficient charge-transport at aggregation-less packing. Hence, the ΔV nr decreases from 0.242 to 0.182 V, from MPhS-C6 to MPhS-C2 based OSCs. An excellent PCE of 17.11% is obtained by 1,8-diiodoctane addition due to almost unchanged high J sc (26.6 mA cm –2 ) and V oc (0.888 V) with improved fill factor, which is the record efficiency with the smallest energy loss (0.497 eV) and ΔV nr (0.192 V) in all-small-molecule OSCs. Finally, these results emphasize the potential material design direction of obtaining concurrent TA-insensitive aggregation and condensed packing to maximize the device performances with a super low ΔV nr .

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enhanced Attenuation of Uranium in the Subsurface

Over time, the focus for the Hanford Site has moved from production to decommissioning and site remediation. Several hundred metric tons of near-surface vadose zone sediment have been excavated from the 300 Area in an effort to remove the source of the uranium contamination (DOE/RL, 2011). Despite remediation efforts, uranium continues to be problematic with concentrations greater than the maximum contaminant level (MCL, which is 30 µg/L) for drinking water. Due to the close proximity of the Columbia River, the uranium continues to be a focus of investigation and remediation. After finding that the uranium concentrations were not decreasing as quickly as expected (based on the 1996 ROD) the Tri-Parties set new milestones, including an update of the conceptual model for the 300 Area uranium plume (Williams et al., 2007). In order to more accurately complete a feasibility study and identify how to remediate the uranium in the groundwater, the DOE authorized a remedial investigation/feasibility study (RI/FS). RI/FSs are designed to screen technologies to determine effectiveness, implementability, and cost (see Chapter 2b). These studies are designed to be conducted concurrently as part of the CERCLA process, so the data collected during site characterization (part of the RI) can inform the treatability studies and field tests conducted under the FS (EPA 1988). For the 300 Area, this study included laboratory, field, and modeling components as well as additional sediment and groundwater characterization to determine a suitable remediation strategy to reduce the uranium concentration in the groundwater plume within the expected time frame and cost.

300 area, uranium, polyphosphate, Hanford book pro↗

DOE OSTI2025

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

A Computational Framework for Control Co-Design of Resilient Cyber–Physical Systems With Applications to Microgrids

Critical infrastructure networks, such as power and transportation networks, can be modelled as cyber-physical systems. As the complexity of such systems grow, there is need for developing metrics and design tools that will co-optimize the physical components of the system and the control policies to guarantee resilience against cyber and natural threats. To that end, we develop a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives. Here, the capabilities of the developed co-design engine is demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Scalable Control Co-design for Resilient-by-Design Cyber Physical Systems

Critical infrastructure networks, such as power and transportation networks, are often modelled as cyber-physical systems. With ever increasing complexity of these systems, there is a need for newer and more relevant metrics and design tools that will co-optimize the physical system components and control policies to guarantee resilience against cyber and natural threats. To this end, a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives has been developed. The capabilities of the developed co-design engine are demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

42 ENGINEERING↗

DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

DOE OSTI2027

Conceptual design of highly-constrained splitters for the FFA@CEBAF energy upgrade study

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is investigating a significant energy upgrade utilizing Fixed-Field Alternating-gradient (FFA) recirculating arcs. This upgrade requires the design of complex horizontal beam splitters to manage up to six concurrent beam passes. This paper presents the conceptual design of these splitters, which are subject to severe physical constraints imposed by the existing accelerator tunnel and multifaceted beam dynamics requirements for matching into the permanent-magnet FFA arcs. The design methodology, centered on multi-pass simulations in the Bmad toolkit, is detailed from the initial geometric layout through the advanced optics matching. Key results include a robust geometric arrangement that fits within the spatial boundaries and the development of multiple, flexible optics matching solutions. Furthermore, the design integrates a viable scheme for extracting high-energy beams for the experimental halls, a critical operational requirement. This work establishes a comprehensive and viable conceptual design, forming a baseline for future engineering and performance optimization studies.

Bodenstein, R.M. [Thomas Jefferson National Accele↗

DOE OSTI2023

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.

Young, Aaron↗

DOE OSTI2021

Evolution of Permeability in Sandstone During Confined Brazilian Testing

Permeability measurements were made on sandstone during confined Brazilian strength tests. The test involves 50 mm diameter disk-shaped, jacketed samples that are subjected to confining stresses while they are diametrically loaded. Specially designed end caps allow for concurrent gas flow measurements. The test configuration allows for the samples to be subjected to a range of stresses, with the confining stress as the intermediate principal stress. Furthermore, the majority of the tests measured permeability during loading to failure in the confined extension region. The permeability of the sandstone sample increases significantly well before the peak load is reached due to newly formed microcracks that continue to coalesce and dilate with further loading. Permeability increases are inversely proportional to the intermediate principal stress as increased confining pressures suppress growth, coalescence, and dilation of microcracks. Additional testing includes unloading and reloading cycles prior to failure. With each unloading–reloading cycle, permeability at comparable stresses is increased compared to the previous cycle, consistent with increasing damage in the form of an expanding microcrack network.

58 GEOSCIENCES↗

DOE OSTI2026

On-chip probabilistic inference for charged-particle tracking at the sensor edge

Modern scientific instruments operate under increasingly extreme constraints on bandwidth, latency, and power. Inference at the sensor edge determines experimental data collection efficiency by deciding which information to save for further analysis. Particle tracking detectors at the Large Hadron Collider exemplify this challenge: pixelated silicon sensors generate rich spatiotemporal ionization patterns, yet most of this information is discarded due to data-rate limitations. Concurrently, advancements in co-design tools provide rapid turn-around for incorporating machine learning into application-specific integrated circuits, motivating designs for particle detectors with new integrated technologies. We demonstrate that neural networks embedded in the front-end electronics can infer charged-particle kinematic parameters from a single silicon layer. We regress hit positions and incident angles with calibrated uncertainties, while satisfying stringent constraints on numerical precision, latency, and silicon area. Our results establish a path toward probabilistic inference directly at the edge, opening new opportunities for intelligent sensing in high-rate scientific instruments.

Das, Arghya Ranjan [Purdue U.] (ORCID:000000018451↗

DOE OSTI2024

Synthesis of Correct Digital Controller Models from Specifications by Model Transformation (21-0320)

The design of high consequence controllers (in weapons systems, autonomy, etc.) that do what they are supposed to do is a significant challenge. Testing simply does not come close to meeting the requirements for assurance. Today circuit designers at Sandia (and elsewhere) typically capture the core behavior of their components using state models in tools such as STATEFLOW. They then check that their models meet certain requirements (e.g. “The system bus must not deadlock” or “both traffic lights at an intersection must not be green at the same time”) using tools called model checkers. If the model checker returns “yes” then the property is guaranteed to be satisfied by the model. However, there are several drawbacks to this industry practice: (1) there is a lot of detail to get right, this is particularly challenging when there are multiple components requiring complex coordination (2) any errors returned by the model checker have to be traced back through the design and fixed, necessitating rework, (3) there are severe scalability problems with this approach, particularly when dealing with concurrency. All this places high demands on the designers who now face not only an accelerated schedule but also controllers of increasing complexity. This report describes a new and fundamentally different approach to the construction of safety-critical digital controllers. Instead of directly constructing a complete model and then trying to verify it, the designer can start with an initial abstract (think “sketch”) model plus the requirements, from which a correct concrete model is automatically synthesized. There is no need for post-hoc verification of required functional properties. Having tool to carry this out will significantly impact the nation’s ability to ensure the safety of high-consequence digital systems. The approach has been implemented in a prototype tool, along with a suite of examples, including ones that reflect actual problems faced by designers. Our approach operates on a variant of Statecharts developed at Sandia called Qspecs. Statecharts are a widely used formalism for developing concurrent reactive systems, supporting scalability through allowing state models containing composite states, which are the serial or parallel composition of substates which can themselves contain statecharts. Statecharts enable an incremental style of development, in which states are progressively refined to incorporate greater detail in an incremental model of software development. Our approach formulates a set of constraints from the structure of the models and the requirements and propagates these constraints to a fixpoint. The solution to the constraints is an inductive invariant along with guards on the transitions. We also show how our approach extends to implementation refinement, decomposition, composition, and elaboration. We currently handle safety requirements written in LTL (Linear Temporal Logic)

42 ENGINEERING↗

DOE OSTI2023

A Revised International Standard for Gearboxes in Wind Turbine Systems

Gearbox and wind turbine design and application standards have contributed significantly to improvements in reliability over the past two decades. The International Electrotechnical Commission (IEC) 61400-4 standard of wind turbine gearbox design is currently being revised by a joint working group (JWG) of experts in IEC TC 88 (wind energy) and International Organization for Standardization (ISO) TC60 (gears) to further that effort. Experts from ISO TC4 (rolling bearings) and ISO TC28 (lubricants) have actively participated. This revision has implemented lessons learned from industry use of edition 1 since its publication in 2012. The main document, IEC 61400-4, was pared down to essential design requirements and application-specific recommendations along with a design verification framework. The JWG leveraged concurrent development of other standards, such as IEC 61400-8 on wind turbine structures, to replace edition 1 content. These are described along with how this works with the IEC Renewable Energy certification scheme for wind turbines (IECRE-WE). The JWG recognized the interest in maintaining informative parts of edition 1 including annexes on wind turbine architecture and loads, bearing and gear arrangements, bearing selection, lubrication system descriptions and lubricant performance recommendations. This information was retained in two technical reports: IEC/TR 61400-4-2 Lubrication and IEC/TR 61400-4-3 Explanatory Notes. Additionally, a technical specification, IEC/TS 61400-4-1, was drafted to provide a reliability calculation method for comparing different design options or conditions. Salient elements of these documents are described. All four documents were recently distributed for IEC/ISO review, ballot, and comment. Publication is expected in 2023.

gearbox↗

DOE OSTI2023

A Revised International Standard for Gearboxes in Wind Turbine Systems: Preprint

Gearbox and wind turbine design and application standards have contributed significantly to improvements in reliability over the past two decades. The International Electrotechnical Commission (IEC) 61400-4 standard of wind turbine gearbox design is currently being revised by a joint working group (JWG) of experts in IEC TC 88 (wind energy) and International Organization for Standardization (ISO) TC60 (gears) to further that effort. Experts from ISO TC4 (rolling bearings) and ISO TC28 (lubricants) have actively participated. This revision has implemented lessons learned from industry use of edition 1 since its publication in 2012. The main document, IEC 61400-4, was pared down to essential design requirements and application-specific recommendations along with a design verification framework. The JWG leveraged concurrent development of other standards, such as IEC 61400-8 on wind turbine structures, to replace edition 1 content. These are described along with how this works with the IEC Renewable Energy certification scheme for wind turbines (IECRE-WE). The JWG recognized the interest in maintaining informative parts of edition 1 including annexes on wind turbine architecture and loads, bearing and gear arrangements, bearing selection, lubrication system descriptions and lubricant performance recommendations. This information was retained in two technical reports: IEC/TR 61400-4-2 Lubrication and IEC/TR 61400-4-3 Explanatory Notes. Additionally, a technical specification, IEC/TS 61400-4-1, was drafted to provide a reliability calculation method for comparing different design options or conditions. Salient elements of these documents are described. All four documents were recently distributed for IEC/ISO review, ballot, and comment. Publication is expected in 2023.

ENGINEERING,WIND ENERGY↗

DOE OSTI2026

Fact Inventory

API to store fact iA lightweight API service built with Litestar for collecting and storing system information from remote hosts. Designed to handle large-scale concurrency, the service receives HTTP submissions of system facts and package inventory from Ansible, curl, or other client tooling.nformation

Riehecky, Pat [Fermi National Accelerator Laborato↗