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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Nanoscaled Components for Improved Efficiency in a Multiplanel Photocatalytic Water-Splitting System

The goal of this program was to construct a multicell photochemical device for the direct conversion of solar energy directly to hydrogen by water splitting. We have fabricated a practical photolytic system for quantum efficient production of hydrogen. Our approach is based on the assembly of a multi-component integrated system for direct photocatalytic splitting of water for the efficient production of hydrogen. We propose to produce hydrogen as an energy source that is cost competitive with fossil fuels and without the concomitant production of greenhouse gases. The concept is quite straightforward. In order to achieve the over potential required for direct water splitting, the device is composed of multiple dye-sensitized cells directly linked in series, as illustrated in the figure below. The advantage of this concept is that each cell need contribute only a fraction of the overall potential required for water splitting, thus permitting device engineering to maximized efficiently without regard to electric potential. Progress and barriers to practical application will be described.

14 SOLAR ENERGY↗
DOE OSTI2018

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts, media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE's with a higher number of variables and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

ACCELERATED DEPLOYMENT OF NOVEL MATERIALS BASED ON RELIABILITY INTEGRITY MANAGEMENT USING CUMULATIVE DAMAGE MODELING

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the 2019 ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain remaining technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. A modeling approach potentially applicable to item (b), based on cumulative damage modeling rather than failure rates, is briefly illustrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Authentication Protocol for ICS without Encryption

Industrial control systems (ICS) describes the different types of control systems and associated instrumentation, which includes the devices, systems, networks, and controls used to operate and/or automate industrial processes. Depending on the industry, each ICS functions differently and are built to electronically manage tasks efficiently. Historically, industrial plants have included networking, and changes have been made over time without consideration for security. Many ICS devices currently have inadequate security features. Adding encryption in ICS is undesirable because many of the new detection method involves deep packet inspection. Therefore, we propose to develop a method of providing authentication between devices without encrypting the data. This testbed design will allow rapid development and experimentation with Cyber Physical Systems. Modbus connects to a supervisory computer with a Remote Terminal Unit (RTU) in Supervisory Control and Data Acquisition (SCADA) systems. Our project seeks to enhance security in the ICS environment by adding device authentication to the lower levels of the plant floor. This approach was selected as it allows verification of the sender of data from level 1/level 0 devices up to supervisory systems. This addition is desirable as it adds enhanced verification to the integrity of system data without obscuring (via encryption) the data being transmitted across the network. This is important because many ICS systems are real time critical (decryption adds to latency) and many other good security options require deep packet inspection (which encryption completely defeats). To accomplish this, a proof of concept of adding an authentication scheme was designed and will be tested with a common ICS protocol. The setup includes a single serial cable connecting the serial ports on two devices, a Master and a Minion. Authentication will occur in the following methods: - Data layer involving Transport Layer Security/Secure Socket Layer (TLS/SSL); - TCP/IP route implementation; - Key exchange algorithm; - Raspberry Pi programming for authentication. A portion of the setup includes adding Raspberry Pi into the system as the device is handling the authentication for the network traffic. Modbus is the chosen ICS protocol. It is used to transmit signals from instrumentation and control devices back to a main controller or data gathering system. Typically, the device identity is assumed but not verified. For verifying device identity, we constructed a digital signature architecture with TLS. A novel adaptation of this is to use only the digital signature that is provided and not the encryption capability. This allows ICS traffic to flow unobscured while still providing verification for the integrity of the data. Verification of this process will involve adding additional I/O level network devices with spoofed IP addresses and detecting the authenticated versus unauthenticated traffic. Our TLS implementation will have encryption disabled but should still allow for digital signing of data. This will enable our system to distinguish between real end devices and spoofed end devices. This experiment is presently building the test setup. It is focusing on a small setting to identify authenticated and unauthenticated devices on the network. This should allow for scaling to a larger network size after the initial proof of concept. One concern with this scheme is a certificate deployment has a large scale key management. Network size will thus increase the key management task for security. In addition, we believe that further research should be done on exploring the use of this method to defeat man-in-the-middle attacks.

42 ENGINEERING↗
DOE OSTI2017

Technology Implementation Plan: Irradiation Testing and Qualification for Nuclear Thermal Propulsion Fuel

This document is a notional technology implementation plan (TIP) for the development, testing, and qualification of a prototypic fuel element to support design and construction of a nuclear thermal propulsion (NTP) engine, specifically its pre-flight ground test. This TIP outlines a generic methodology for the progression from non-nuclear out-of-pile (OOP) testing through nuclear in-pile (IP) testing, at operational temperatures, flows, and specific powers, of an NTP fuel element in an existing test reactor. Subsequent post-irradiation examination (PIE) will occur in existing radiological facilities. Further, the methodology is intended to be nonspecific with respect to fuel types and irradiation or examination facilities. The goals of OOP and IP testing are to provide confidence in the operational performance of fuel system concepts and provide data to program leadership for system optimization and fuel down-selection. The test methodology, parameters, collected data, and analytical results from OOP, IP, and PIE will be documented for reference by the NTP operator and the appropriate regulatory and oversight authorities. Final full-scale integrated testing would be performed separately by the reactor operator as part of the preflight ground test.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Lessons Learned From Ventilation and Glovebox Flooding Via Overfilling of the Wet Vacuum System in a Plutonium Facility

In the summer of 2021, operations personnel requested maintenance personnel to fill a wet vacuum (Wetvac) seal water tank in a plutonium facility at Los Alamos National Laboratory (LANL). After the filling was finished, the fill valve of the Wetvac seal water tank was left open and a ‘dead-man’ valve on an isolation line failed to close properly. After a series of other failures, the water exited the glovebox and contaminated three rooms of the first floor of the facility and an underlying area in the basement. A retrospective analysis of this event determined that there was no risk of a criticality due to the inherent design features of the ventilation system. This paper will explain the driving factors behind how this event was able to happen, as well as some of the major lessons learned that can be universally applied to other nuclear facilities. One of the main causes of the event was the delegation of work to maintenance personnel that were not qualified for the work being asked of them. Additionally, there was a lack of coordination between criticality safety engineers and facility operations equipment owners regarding equipment and connections present on the seal water tanks for the Wetvac, specifically the presence of overflow drain lines. The respective criticality safety evaluation credited an overflow drain line being present on the seal water tanks that was later found to have not been present. Lastly, there are lessons to be learned regarding equipment configuration and designing systems with safety in mind.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2012

Mission and Readiness Assessment for Fusion Nuclear Facilities

Magnetic fusion development toward DEMO will most likely require a number of fusion nuclear facilities (FNF), intermediate between ITER and DEMO, to test and validate plasma and nuclear technologies and to advance the level of system integration. The FNF mission space is wide, ranging from basic materials research to net electricity demonstration, so there is correspondingly a choice among machine options, scope, and risk in planning such a step. Readiness requirements to proceed with a DEMO are examined, and two FNF options are assessed in terms of the contributions they would make to closing DEMO readiness gaps, and their readiness to themselves proceed with engineering design about ten years from now. An advanced tokamak (AT) pilot plant with superconducting coils and a mission to demonstrate net electricity generation would go a long way toward DEMO. As a next step, however, a pilot plant would entail greater risk than a copper-coil FNSF-AT with its more focussed mission and technology requirements. The stellarator path to DEMO is briefly discussed. Regardless of the choice of FNF option, an accompanying science and technology development program, also aimed at DEMO readiness, is absolutely essential.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Integrating commercially available remote systems to address current D and D challenges - 15399

Many current D and D challenges across the DOE complex require some form of remote handling expertise and equipment. For example, high visibility projects such as Building 324 D and D and the recovery of wastes from the Alpha-Caissons and the 618 10-11 caissons at Hanford all require the development and application of advanced remote systems. Additionally although alternate solutions and options are being sought, robotic/remote systems will likely be required for completion of D and D at Savannah River Site's Building 235-F, at the West Valley Demonstration Project and many other DOE facilities that are scheduled for D and D. Similar systems are also needed to support the UK cleanup program on projects such as the decommissioning of the Pile Fuel Cladding Silo. As a result, there are a significant number of R and D and Technology Development projects underway in order to address the growing need for remote systems in D and D. In addition to these significant R and D efforts, there are also numerous remote systems in use in multiple applications in both nuclear and non-nuclear industries and the use of remote systems at the Fukushima Daiichi plant has been extensive in the past 12-24 months. In many cases, the systems developed are customized for their given application but there are also multiple systems in use which could be applied to the worldwide D and D challenge either directly or with some minor adaptation. During FY14, the Office of D and D and Facility Engineering (EM13) funded a review/assessment of the current state-of-the-art of robotics and remote technologies in order to generate a baseline of what is available, what has been used where and for what applications and what has been successful and what hasn't. Where possible, the assessment was extended to identify remote systems that have been used in non-nuclear industries but which, with limited modification, may have application in the nuclear industry. The work also included a review of the most recent publicly available TBuRD (Technical Baseline and Underpinning R and D) activities being undertaken by the UK NDA and their Site Licensed Companies (SLCs) in the area of remote systems in order to compile a searchable database of both available, commercial-off-the-shelf (COTS) remote systems and developing technologies. Other suitably qualified organizations in the US and the UK (such as UK National Nuclear Laboratory, SRNL, PNNL ORNL, OC Robotics and others) were also engaged to identify other ongoing technology development efforts which may be of interest and benefit to the decommissioning community. In all, of the order of 500 remote systems were identified and cataloged in both hard copy and as a searchable database. These systems were categorized in terms of their main application e.g. manipulator, wheeled land-based platform, track land-based platform, water-based platform, air-based platform, end effectors, sensor, crawler etc to clearly demonstrate the depth and breadth of available systems in each category. In addition, single page summaries of each system were produced and used, in a workshop setting, to identify technologies which, when integrated with other currently-available technologies, could provide a workable system to address existing needs. An initial workshop was held with CH2 Washington Idaho (CWI) and DOE Idaho in August 2014 to explore how the available systems could be integrated to address current and future D and D needs at that site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Manufacturing Demonstration Facility: Development and Evaluation of Hybrid Manufacturing Toolpaths

The integration of additive manufacturing (AM) capabilities on Computer Numerical Control (CNC) systems allows for the expansion of additive manufacturing to a wide range of part and tool repair operations. This multi-tasking integration, termed hybrid manufacturing, has been researched by others in the past, and Autodesk has been critical in developing process planning and toolpath algorithms for hybrid systems. Objectives and Tasks: Hybrid manufacturing systems enable both additive and subtractive capabilities in a single manufacturing workcell. These systems have the potential to impact a variety of industries, including the tool and die industry due to their repair, refurbishment, and complex geometry manufacturing capabilities. While there has been significant development of toolpath planning for both subtractive and additive processes independently, there has been little, if any, development of hybrid toolpath planning to integrate both processes during the manufacturing design and toolpath generation stage of a product’s lifecycle. Furthermore, additive toolpath planning has been limited to planar manufacturing, but this limitation could be overcome as hybrid CNC machines have multi-axis control. The objectives of this research include: - Development and demonstration of independent three-, four-, and five-axis toolpath generation algorithms for both additive and subtractive processes, and - Development, demonstration, and integration of three-, four-, and five-axis hybrid process planning and toolpath generation algorithms for hybrid additive and subtractive processes. The team will leverage the widely used Autodesk Fusion 360 product design and manufacturing (CAD/CAM) platform to achieve these objectives. Autodesk will provide the expertise in CAD tools, as well as access to their new CAD/CAM manufacturing tools (3-, 4-, and 5-axis milling, additive toolpath generation). ORNL will provide expertise in additive manufacturing toolpath generation, process planning, and manufacturing validation. By the end of the program, the team will have developed and validated multi-axis milling, additive manufacturing, and hybrid manufacturing on an industrial hybrid CNC system (Mazak 500-VC).

42 ENGINEERING↗
DOE OSTI2025

Methanol from Integrated Direct Air Capture and Ceramic Electrolysis (MIDACE)

The Methanol from Integrated Direct Air Capture and Ceramic Electrolysis (MIDACE) project advanced a novel system concept for integrating pressurized co-electrolysis of steam and crude carbon dioxide captured directly from ambient air using a sorbent technology. The co-electrolysis produced syngas provides feedstock for a gas-to-liquid methanol synthesis reactor. The system recovers waste heat from the reactor and electrolyzer into regenerating the direct air capture sorbent. The purpose of the project was to demonstrate critical integration elements of the design and perform a technical study illustrating how a large-scale installation could achieve the $800/ton program target for green methanol production. The concept addresses the program objective to consolidate operations by combining crude CO 2 cleanup, hydrogen production, and partial CO 2 reduction steps within a carbon tolerant high temperature electrolyzer. The design lowers costs by simplifying the methanol recovery cycle, reducing carbon losses from venting, reducing sensitivity to catalyst selectivity, and avoiding syngas compression.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Integrated membrane material design and system synthesis

In designing membrane systems, the synergy between membrane materials and the process design is often overlooked. In this paper, we present a mixed-integer nonlinear programming (MINLP) model for synthesizing membrane systems while simultaneously designing the respective membrane materials for multicomponent gas separation. The approach considers superstructure representations for systems with: (1) same, (2) potentially different, and (3) property-targeting membrane materials. In the first two systems, the selection of membrane material is a decision, while in the final type, membrane permeances are subject to optimization. Physics-based surrogate models are used to describe permeation in crossflow and countercurrent flow permeators. We show that, through a case study of biogas upgrading, our approach obtains high quality solutions. Furthermore, we use the proposed approach while considering permeance-based production cost to find the optimal membrane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

Agricultural Sciences↗
DOE OSTI2018

Phenomena identification and ranking table study for thermal hydraulics for Advanced High Temperature Reactor

The Advanced High-Temperature Reactor (AHTR) is a conceptual design of a Fluoride salt-cooled High-temperature Reactor (FHR) utilizing 7 LiF-BeF 2 (66-34 mol%) as its primary coolant. To identify key phenomena that impose potential challenges on thermal hydraulics modeling and simulation of such a reactor system, a thermal hydraulics phenomena identification and ranking table (TH-PIRT) study was performed for the AHTR in a Department of Energy Nuclear Energy University Program (NEUP) integrated research project led by Georgia Institute of Technology. A panel of experts from regulators, industries, national laboratories, and academia was assembled for the study. In this paper, the TH-PIRTs identified by the panel for two events, namely, station blackout and simultaneous withdrawal of all control rods, are summarized and discussed in detail. In addition, the key phenomena that warrant further study and research for AHTR analysis are identified to support the validation of thermal hydraulics system-level analysis codes and computational fluid dynamics simulation tools, as well as future FHR reactor licensing.

42 ENGINEERING↗
DOE OSTI2022

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Towards A Unified HFE Process For The Nuclear Industry

As nuclear power utilities embark on projects to upgrade and modernize power plants, they are likely to discover that traditional engineering methods do not typically make provision for the integration of human considerations. In addition, human factors professionals will find that traditional human performance methods such as function allocation, task analysis, human reliability analysis and human-machine interface design do not scale well to the complexity of a large-scale nuclear power upgrade project. Up-to-date human factors engineering processes, methods, techniques and tools are required to perform these kinds of analyses. This need is recognized widely in industry and an important part of the Department of Energy’s Light Water Reactor Sustainability Program deals with identifying potential impacts of emerging technologies on human performance and the technical bases needed to address them. However, so far no formal initiative has been launched to deal with the lack of integrated processes. Although human factors integration frameworks do exist in industries such as aviation or defense, no formal integrated human factors process exists in the nuclear industry. As a first step towards creating such a process, a “unified human factors engineering process” is proposed as a framework within which engineering organizations, human factors practitioners and regulatory bodies can ensure that human factors requirements are embedded in engineering activities throughout the upgrade project life cycle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗