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At least 1,081 records · Page 60

Update on Parallel Process Execution in the Next Generation System Analysis Model (NGSAM)

As of the end of 2022, it is estimated that over 90,000 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) were stored at various commercial nuclear power reactor sites (both operating and shutdown) across the United States [1]. The Office of Storage and Transportation within the U.S. Department of Energy’s Office of Nuclear Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, available facilities, start dates, interim storage capacity, etc.) and study the associated system implications such as timing for clearing sites of SNF, various cost elements, transportation infrastructure acquisition needs, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Engineering Cyanobacterial Cell Morphology for Enhanced Recovery and Processing of Biomass

Cyanobacteria are emerging as alternative crop species for the production of fuels, chemicals, and biomass. Yet, the success of these microbes depends on the development of cost-effective technologies that permit scaled cultivation and cell harvesting. Here, we investigate the feasibility of engineering cell morphology to improve biomass recovery and decrease energetic costs associated with lysing cyanobacterial cells. Specifically, we modify the levels of Min system proteins in Synechococcus elongatus PCC 7942. The Min system has established functions in controlling cell division by regulating the assembly of FtsZ, a tubulin-like protein required for defining the bacterial division plane. We show that altering the expression of two FtsZ-regulatory proteins, MinC and Cdv3, enables control over cell morphology by disrupting FtsZ localization and cell division without preventing continued cell growth. By varying the expression of these proteins, we can tune the lengths of cyanobacterial cells across a broad dynamic range, anywhere from an ~20% increased length (relative to the wild type) to near-millimeter lengths. Highly elongated cells exhibit increased rates of sedimentation under low centrifugal forces or by gravity-assisted settling. Furthermore, hyperelongated cells are also more susceptible to lysis through the application of mild physical stress. Collectively, these results demonstrate a novel approach toward decreasing harvesting and processing costs associated with mass cyanobacterial cultivation by altering morphology at the cellular level. We show that the cell length of a model cyanobacterial species can be programmed by rationally manipulating the expression of protein factors that suppress cell division. In some instances, we can increase the size of these cells to near-millimeter lengths with this approach. The resulting elongated cells have favorable properties with regard to cell harvesting and lysis. Furthermore, cells treated in this manner continue to grow rapidly at time scales similar to those of uninduced controls. To our knowledge, this is the first reported example of engineering the cell morphology of cyanobacteria or algae to make them more compatible with downstream processing steps that present economic barriers to their use as alternative crop species. Therefore, our results are a promising proof-of-principle for the use of morphology engineering to increase the cost-effectiveness of the mass cultivation of cyanobacteria for various sustainability initiatives.

59 BASIC BIOLOGICAL SCIENCES↗

An Accurate, Error-Tolerant, and Energy-Efficient Neural Network Inference Engine Based on SONOS Analog Memory

In this work, we demonstrate SONOS (silicon-oxide-nitrideoxide- silicon) analog memory arrays that are optimized for neural network inference. The devices are fabricated in a 40nm process and operated in the subthreshold regime for in-memory matrix multiplication. Subthreshold operation enables low conductances to be implemented with low error, which matches the typical weight distribution of neural networks, which is heavily skewed toward near-zero values. This leads to high accuracy in the presence of programming errors and process variations. We simulate the end-to-end neural network inference accuracy, accounting for the measured programming error, read noise, and retention loss in a fabricated SONOS array. Evaluated on the ImageNet dataset using ResNet50, the accuracy using a SONOS system is within 2.16% of floating-point accuracy without any retraining. The unique error properties and high On/Off ratio of the SONOS device allow scaling to large arrays without bit slicing, and enable an inference architecture that achieves 20 TOPS/W on ResNet50, a >10× gain in energy efficiency over state-of-the-art digital and analog inference accelerators.

97 MATHEMATICS AND COMPUTING↗

HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids

Here, this paper presents a refined quantum Harrow Hassidim Lloyd (HHL) algorithm for microgrid control. The first novelty of the developed method is that a mapping shift function enables the original HHL algorithm to handle general linear equations with non-singular and indefinite matrix. Second, a method of Matrix Extension for Amplifying Sampling Probabilities of Intended Solution (ME-ASPI) is proposed to design the reformulated linear algebraic equations, allowing for improved sampling efficiency of the quantum tomography in the refined HHL algorithm. Then, we applied the method to solve the model predictive control (MPC) problem in nonlinear dynamical microgrids. Specifically, with the ME-ASPI method, the refined HHL algorithm can effectively obtain the intended partial optimal control inputs for MPC. The optimization of quadratic programming problem in each time step of MPC is transformed into a linear system problem, which is addressed by the proposed quantum solver through using only partial information, with the time complexity improved from $\mathscr{O}(\mathscr{N}^{2.37286})$ classically to $\mathscr{O}(\mathscr{N}^{2} log \mathscr{N}$ x $p$ log $p)$ in quantum. Numerical examples have validated the effectiveness of the refined HHL algorithm with the proposed mapping function and the ME-ASPI method. By leveraging quantum properties, the proposed method provides a hybrid quantum–classical framework for microgrid control. This generic method can also potentially tackle many other challenges in analyzing and controlling general complex engineered systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Memory forensic analysis of a programmable logic controller in industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLCs) are used to automate physical processes such as nuclear plants and power grid stations, and are often subject to cyber attacks. As in conventional IT domain, the memory analysis of the PLCs can help answer important forensic questions about the attack, such as the presence of malicious firmware, injection of modified control logic (the program running on the PLC), and manipulation of I/O devices (e.g., sensors and actuators). Unlike conventional IT domain, PLCs have heterogeneous hardware architecture, proprietary firmware and control software, making it challenging to employ a unified framework for their memory forensics. For merely extracting artifacts of forensic importance, reverse-engineering the firmware is a tedious task, and the effort needs to be repeated for every PLC model. As a community, a step-wise approach to tackle this challenge is to analyze the memory of specific PLCs, and subsequently find a generic framework applicable to all PLCs. Our work is a step forward in this direction. By following a methodology that focuses on the functional layer of PLCs instead of reverse engineering the firmware, we analyze the digital forensic artifacts available in a common PLC, Allen-Bradley ControlLogix 1756-L61. Before diving into the memory dump, we analyze the PLC control software to create a list of important artifacts that are sure to exist in the PLC memory dump. The approach employs a setup where PLC control software RSLogix-5000 is connected to the PLC, and the memory dump can be obtained as and when needed. We create test cases that sequentially highlight each category of artifacts, followed by an examination of the resultant impact on memory. After attaining the listed artifacts, we employ conventional string and known data searches to extract interesting information present in this PLC's memory. The memory analysis profile, presented as a Python library and shared with the community, can help a forensic investigator to readily extract forensic artifacts from the same model's controller. The adopted approach may help researchers in creating memory profile of other PLCs, and ultimately formulating a generic PLC memory analysis framework.

Rais, Muhammad Haris↗

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

BOPTEST as a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

A Case Study in the Application of TSUNAMI-3D Part 1, Multigroup

The use of the sensitivity and uncertainty tool suite within SCALE, known as the TSUNAMI suite, has grown following its initial introduction more than a decade ago. Proper use of these tools provides a more complete understanding of system responses to perturbations, especially in the area of nuclear cross section uncertainties. Recent advances within TSUNAMI have added generalized perturbation theory to the keff sensitivity capability that was included in TSUNAMI originally. The generation of sensitivity data is encouraged in the review process for new critical experiment requests sponsored by the US Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP)to demonstrate that the proposed experiment will satisfy the identified data need. Many individuals participate in this process, but many analysts have not received proper training in the use of the TSUNAMI tools. The adjoint perturbation theory used to calculate sensitivities is not typically included in nuclear engineering curricula, leaving inexperienced engineers particularly at risk for incorrect use of the tools.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies, software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.

54 ENVIRONMENTAL SCIENCES↗

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

99 - GENERAL AND MISCELLANEOUS↗

FY 2014 Annual Progress Report - Advanced Combustion Engine Research and Development (Book)

In the past year, the DOE Hydrogen Program (the Program) made substantial progress toward its goals and objectives. The Program has conducted comprehensive and focused efforts to enable the widespread commercialization of hydrogen and fuel cell technologies in diverse sectors of the economy. With emphasis on applications that will effectively strengthen our nation's energy security and improve our stewardship of the environment, the Program engages in research, development, and demonstration of critical improvements in the technologies. Highlights of the Program's accomplishments can be found in the sub-program chapters of this report.

08 HYDROGEN↗

Am-241 Nuclear Safety and Environmental Interactions

NASA’s supply of radioisotopes for Radioisotope Heat Units (RHU) and Radioisotope Thermoelectric Generator (RTG) power sources is facing a crisis due to shortages of Pu-238 for future missions. Am-241 is a possible replacement for Pu-238 since its stockpile from the nuclear weapons program has remained relatively intact. The purpose of this project was to assess the safety of Am-241 and the risks associated with it as compared with PU-238. The project has resulted in a journal article, F. De-La-Torre-Aguilar, N. White, M. Prelas, R. V. Tompson, and S. K. Loyalka "Space nuclear power system accidents: Doses from Pu-238 and Am- 241 inhalation," Progress in Nuclear Energy vol.100C (2017), pp.171-182, which showed that the radiation dosage resulting from Am-241 inhalation are about 1/2.5 of the dosage resulting from Pu-238 inhalation per KW of Pu-238 power. Considerable progress was also made on the Direct Simulation Monte Carlo Method (DSMC) for simulation of aerosol evolution during accidents resulting in three publications: 1.I. Saldivar, F. De-La-Torre-Aguilar, M. Boraas, and S. K. Loyalka “Benchmark problems in aerosol evolution: Comparison of some exact and DSMC results” in Annals of Nuclear Energy vol.117 (2018), pp.213-222. 2. I. Saldivar and S. K. Loyalka, “Evolution of Aerosols Coupled to Environments: Verification of Direct Simulation Monte Carlo (DSMC)”, Nuclear Technology 204 (2018), pp.172-183. 3. M. Boraas and S. K. Loyalka, “Mesh Free Simulation of Spatially Inhomogeneous aerosols in Arbitrary Geometries” Nuclear Science and Engineering (2018). Further, we have computations on Am-241/Pu-238 vapor and aerosol interactions, and found that the vapor condensation rate is relatively insensitive to the mass effects, confirming some previous results. We have also completed computations of charge effects on evolution of different species aerosols and a manuscript is in preparation. Additionally, we have compared atmospheric dispersion and deposition of Pu-238 and Am-241 using the HYSPLIT code. We have also used a real lung model and the CFD program FLUENT to compute PuO2 and AmO2 deposition to explore improvements upon the ICPR-66 model. We have found that the deposition efficiencies of PuO2 and AmO2 are similar. These results (four manuscripts) will be submitted for publication in the post project period. We have made progress using framework of Mars 2020 mission nuclear risk assessment model to integrate all results, but our progress has been limited as the improved consequence modeling itself has been quite involved and challenging. We will integrate and complete the more extensive risk modeling computations and publish the results in the post-project period. In addition to the above, the project has resulted in research training of four PhD students

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Impact of Active Control on Passive Safety Response Characteristics of Sodium-cooled Fast Reactors: I - Theoretical background

Here, the interaction of the active control system with passive safety behavior is investigated for sodium-cooled fast reactors. A claim often made of advanced reactors is that they are passively safe against unprotected upset events. In practice, such upset events are not analyzed in the context of the plant control system, but rather the analyses are performed without considering the normally programmed response of the control system (open-loop approach). This represents an oversimplification of the safety case. The issue of passive safety override arises since the control system commands actuators whose motions have safety consequences. Depending on the upset involving the control system ( operator error, active control system failure, or inadvertent control system override), an actuator does not necessarily go in the same direction as needed for safety. So neglecting to account for control system action during an unprotected upset is nonconservative from a safety standpoint. It is important then, during the design of the plant, to consider the potential for the control system to work against the inherent and safe regulating effects of purposefully engineered temperature feedbacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Molten Salt Reactor Experiment (MSRE) Lay-Up - 19187

UCOR, an AECOM-led partnership with Jacobs, manages the cleanup of the 2,200-acre East Tennessee Technology Park for its client, the U.S. Department of Energy (DOE), in Oak Ridge, Tennessee. The site was contaminated with radioactive, hazardous and industrial wastes generated by more than 40 years of national defense and energy missions. 2019 is the 50. anniversary of the shutdown of the Molten Salt Reactor Experiment (MSRE). MSRE ran a brief four years in the 1960's but earned an enduring legacy as an innovative reactor technology concept which has enjoyed a renewal of global interest in the past several years. In 2018, it was given elevated status among advanced reactor programs within DoE's Nuclear Energy office. The MSRE was a graphite-moderated, liquid fueled reactor that operated from June 1965 through December 1969. Although it was shut down nearly 50 years ago, certain systems within the reactor have continued to operate to maintain the facility in a safe and stable condition until it can be demolished as part of the comprehensive cleanup of the Oak Ridge Reservation. These systems are composed of a complex network of pipes, valves, gauges and associated equipment that control air filtration and pressure buildup resulting from fluorine gas generated through radiolysis of the fluoride salt which once fueled the reactor. In 2016, an MSRE Engineering Evaluation Team was chartered to assess current facility conditions and develop recommendations to maintain the facility in a safe state until deactivation and demolition commences. Plans are now underway to 'lay up' the MSRE facility until deactivation and demolition can occur. The proposed MSRE Facility Layup will minimize maintenance costs, reduce personnel risk of injury and exposure, provide reliable electric service to the facility and require zero personnel occupancy at MSRE. In the proposed layup approach a new source of electrical power to required loads will be routed through the facility, and new gas processing and ventilation systems will be installed that will be optimized for safe processing of the constituent hazardous gasses that exist in the legacy vessels at MSRE. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

ADVANCED CONSTRUCTION TECHNOLOGY INITIATIVE (ACTI)

Advanced reactor technologies have attracted considerable financial support, catalyzing innovation in the nuclear energy landscape. These next generation reactors are designed with enhanced passive safety systems and the potential for cost reductions. As these advanced reactors approach technological maturity, their commercial success also requires focused examination and essential support. Economic assessments in the nuclear energy sector often emphasize construction costs and the risk of scheduling delays as primary contributors to deployment expenditures. Traditionally, vital elements of nuclear energy deployment including civil/structural engineering, design sophistication and automation have been either undervalued or postponed in the development cycles. Additionally, the nuclear industry’s collective experience in nuclear project execution has diminished over the past several decades due to the infrequency of new plant constructions. Hence, The National Reactor Innovation Center’s (NRIC) Advanced Construction Technology Initiative (ACTI) program aims to reduce cost overruns and schedule slippages that have plagued the construction of nuclear power plant projects. With this initiative, NRIC is facilitating the development of advanced nuclear plant construction technologies and approaches through partnerships that would provide game-changing benefits to the construction of advanced nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Finite Element Analysis of the TRUST Nonlinear Dynamics Testbed

This paper builds on prior work conducted within the Los Alamos National Laboratory (LANL) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) program. Specifically, it builds on finite element (FE) modeling efforts for the TRUST program’s Nonlinear Dynamics (ND) testbed. Historically, the FE model for the ND testbed has exclusively utilized a Lanczos eigensolver that linearly extracts the system’s natural frequencies. This paper investigates the Abaqus 2024’s explicit dynamic solver, which implements a central difference explicit solver. The central difference method used in Abaqus can capture nonlinear material responses in structural dynamic simulations making it suitable for the ND FE model.

42 ENGINEERING↗

SB6.0: The 6th International meeting on Synthetic Biology, July 9-11, 2013

The Synthetic Biology conference series (SBx.0) is the preeminent academic meeting in synthetic biology. Organized by the BioBricks Foundation, the SBx.0 conference series brings together leading researchers, students, industry executives, and policy makers from around the world to share, consider, debate, and plan efforts to make biology easier to engineer. Historically held every two years, the SBx.0 conferences are held in alternating locations in the United States, Europe, and Asia to encourage global participation and collaboration so that the ramifications of synthetic biology research and development are most likely to be safe ethical, and beneficial. On 9-11 July 2013, the 6th installment of the synthetic biology conference series (SB6.0) was held on the campus of Imperial College London (http://sb6.biobricks.org). The SB6.0 conference was attended by over 700 people, and many more were able to participate via video digital conference (http://sb6.biobricks.org/digital-conference/). Over the course of three days, the SB6.0 conference agenda included plenary sessions, workshops, and poster presentations covering topics ranging from the infrastructure needs arising when “Systematic Engineering Meets Biological Complexity” and design-led considerations for “Connecting People and Technologies” to discussions on “Engineering Biology for New Materials,” “Assessing Risk and Managing Biocontainment,” and “New Directions for Energy and Sustainability.” The $10,150 grant awarded by the U.S. Department of Energy (DE-SC0010233) to the BioBricks Foundation was used to provide partial reimbursement for the travel expenses of leading researchers from the United States to speak at the SB6.0 conference. A total of $9,450 was used to reimburse U.S. speakers for actual expenses related to the SB6.0 conference, including airfare (economy or coach only), ground transportation, hotel, and registration fees. In addition, $700 of the grant was used to offset direct administrative costs associated with selecting speakers (preparing announcements, evaluating abstract submissions) and handling travel arrangements. Leading U.S. researchers selected to speak at the SB6.0 conference included: Adam Arkin, Ph.D. Division Director of the Physical Biosciences Division at the Lawrence Berkeley National Laboratory and Professor in the Department of Bioengineering at UC Berkeley Jay Keasling, Ph.D. Professor in the Department of Bioengineering at Berkeley, Senior Faculty Scientist and Associate Laboratory Director of the Lawrence Berkeley National Laboratory, and Chief Executive Officer of the Joint BioEnergy Institute. Debra Mathews, Ph.D. Assistant Director for Science Programs for the Johns Hopkins Berman Institute of Bioethics, Assistant Professor in the Department of Pediatrics, and Affiliate Faculty in the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine. Richard Murray, Ph.D. Thomas E. and Doris Everhart Professor of Control & Dynamical Systems and Bioengineering at Caltech. Sarah Richardson, Ph.D. Distinguished Postdoctoral Fellow in Genomics at the Lawrence Berkeley National Laboratory and the Department of Energy Joint Genome Institute. and others (for a complete listing of speakers presenting at the SB6.0 conference see http://sb6.biobricks.org/speakers/) The SB6.0 conference was the largest synthetic biology conference to date, and highlights of the SB6.0 conference have been published in a special issue of ACS Synthetic Biology (http://pubs.acs.org/toc/asbcd6/3/3). The BioBricks Foundation appreciates the support of the U.S. Department of Energy in helping to make this most influential and important conference in the field of synthetic biology a success.

42 ENGINEERING↗