Search NASA⌕ Search

SEARCH · Search NASA

Results for “Maximization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Opportunities and Challenges for Nuclear-Renewable Hybrid Energy Systems

Nuclear-renewable hybrid energy systems (also known as integrated nuclear-renewable systems) are conceptual systems that have two or more energy inputs and produce two or more products. They maximize profitability, and usually equipment utilization, by adjusting between the products depending upon the availability of resources and market value. For example a nuclear-renewable hybrid energy system that produces electricity and hydrogen would maximize sales of electricity when its price is high and shift to hydrogen production when the electricity price is low. This presentation summarizes the results of several economic analyses of nuclear-renewable hybrid energy systems and they key overall conclusions from those analyses.

economic analysis↗
DOE OSTI2021

Regional Hybrid Energy Systems Technoeconomic Analysis

The National Renewable Energy Laboratory (NREL) has been working with the Idaho National Laboratory (INL) and Argonne National Laboratory (ANL) to analyze the potential that hybridizing Xcel Energy's two nuclear power plants in Minnesota might have. The hybrid nuclear power plants would maximize sales of electricity when its price is high and reduce electricity sales to maximize hydrogen production when the price of electricity is low. This presentation summarizes the project's approach and status and communicates future direction.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDROGEN↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration: Preprint

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions, i.e., the reserve requirement, renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained off-line using historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine and battery. Case studies demonstrated that the proposed method outperforms other operating reserve determination methods.

distribution system↗
DOE OSTI2020

Real-time Ridesharing for Transportation Hubs with Demand and Supply Uncertainty

Transportation hubs in major cities generate a significant amount of trips by taxis and for-hail vehicles (FHV), with many of the trips sharing similar destinations. This suggests promising opportunities to leverage the collective travel needs with dedicated ridesharing solutions to reduce the externalities of excessive traffic at transportation hubs. In this study, we develop a novel dynamic ridesharing approach to serve trips from the transportation hub by considering (1) demand (new passengers) and supply (newly available vehicles) in the near future and (2) the uncertainty of future predictions. Our approach consists of two stages. In the first stage, we develop a data structure called hub mobility tree to generate potential combinations of shareable trips as candidate schedules efficiently. Then the generated schedules are used in the second stage to formulate the stochastic hub-based ridesharing problem (SHRP), which is a stochastic integer programming problem with the objective to maximize the total expected ridesharing profit over time. Due to the prohibitive number of shareable trips, we then approximately solve SHRP by the sample average approximate method (SAA), and a dual Lagrangian technique is implemented to further improve the scalability of the solution approach. We demonstrate the performances of the proposed method by simulating the ridesharing service at JFK airport using NYC taxi and FHV data. The results indicate that the proposed method outperforms the myopic ridesharing (maximize profit for a single time step) and the rolling horizon method with point estimation of future demand and supply.

dynamic ridesharing↗
DOE OSTI2022

Single-Axis Tracker Control Optimization Potential for the Contiguous United States: Preprint

Conventional tracker control algorithms maximize collection of direct irradiance with no regard for collection of diffuse irradiance. Therefore, a tracker control algorithm that optimizes for maximal total irradiance, not just direct, might realize improved insolation collection. Using weather data gridded at 0.25° by 0.25° latitude/longitude spacing covering the contiguous United States, we evaluate the insolation gain of two alternative control algorithms optimized for improved total irradiance collection in monofacial arrays and present annual and monthly geographic heatmaps showing the gains across the contiguous United States. Certain locations show potential annual insolation gains approaching 1.0%, but most locations with recently-built tracker systems show annual gains between 0.1% and 0.4%. We also demonstrate a relationship between a climate's annualized diffuse insolation fraction and its potential tracker optimization insolation gain.

diffuse↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.

distribution system↗
DOE OSTI2022

Verification of Upcoming MCNP Features For Estimating Nuclear Data Sensitivities in Fixed Source Simulations [Abstract]

Predictive simulation codes, like the Monte Carlo N-Particle (MCNP) transport code, are used throughout the nuclear community. These simulations are based on nuclear data. Maximizing the accuracy and precision of nuclear data maximizes the accuracy and precision of the overall simulation. This is imperative to applications that rely on simulations. For example, improving nuclear data for special nuclear material improves simulation accuracy in stockpile stewardship applications, which results in larger safety margins and decreased operational costs. The improvement and validation of nuclear data is completed through integral benchmark experiments. Past benchmarks have primarily been limited to focus on the effective multiplication factor ($\kappa$ eff ); broadening the purview of benchmarks beyond $\kappa$ eff -dependent nuclear data addresses nuclear data deficiencies. Different response types depend on different areas of nuclear data. This dependence is quantified as nuclear data sensitivity: the change in response due to perturbation of a contributing parameter. The larger the nuclear data sensitivity of a response, the more the experiment is influenced by the uncertainties of the nuclear data. The optimization of nuclear data sensitivities in future benchmarks would result in more detailed validation of lesser studied areas of nuclear data. Currently, direct sensitivity capabilities are not easily found for all experiment types and parameters. An MCNP tool to directly estimate the cross section sensitivities of tallied values is under development. Additionally, updates have been made to the perturbation feature of MCNP, which can be used in a less direct approach to estimating sensitivities. This work verifies these features to estimate nuclear data sensitivities in fixed source simulations of a 4.5-kg sphere of alpha- phase weapons-grade plutonium surrounded by differing amounts of copper and polyethylene. Integrated estimates made using MCNP’s tools were found to statistically agree with integrated estimates made from manual perturbation of nuclear data proving the validity of the MCNP tools.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Self-tuning wave energy converter (WEC) controller for changing sea states

Systems and methods for a WEC controller that uses a self-tuning proportional-integral control law prescribing motor torques to maximize electrical power generation and automatically tune the controller to maximize power absorption. In an embodiment, the controller may be part of any resonant WEC system. The control law relies upon an identified model of device intrinsic impedance to generate a frequency-domain estimate of the wave-induced excitation force and measurements of device velocities. The control law was tested in irregular sea-states that evolved over hours (a rapid, but realistic time-scale) and that changed instantly (an unrealistic scenario to evaluate controller response).

Bacelli, Giorgio↗
DOE OSTI2017

Exposure Assumptions Underlying Cleanups to Industrial Versus Unrestricted Uses: Comparison of State and Federal Approaches - 17228

The Environmental Protection Agency (EPA) and various states have designated a variety of cleanup levels ranging from restricted (too much residual contamination to allow any use) to unrestricted or residential. Although there are many potential exposure scenarios, the States of Washington and New Jersey identify only two levels for cleanup of chemical contaminants in soil: 'unrestricted' and 'industrial' (Washington) and 'residential' vs 'non-residential' (New Jersey). Other agencies such as EPA and DOE recognize several levels of recreational use, between unrestricted and industrial, and likewise there are several levels of residential use as well. Cleanup criteria may allow or preclude the use of ground water for drinking, swimming pools, gardens, or lawns. Tribal unrestricted scenarios include the use of water (probably surface water in most scenarios) for sweat lodges, and have calculated high level exposure pathways for both dermal and inhalation pathways as well as ingestion. For residential scenarios, inadvertent ingestion of soil, drinking of ground water, and consumption of local foods represent the highest exposure pathways. Intermediate, recreational pathways may be non-consumptive (hiking, bird watching, photography) or consumptive (hunting, fishing, harvesting plants and medicines), the latter entailing much higher potential exposures. For each land-use there is a corresponding exposure scenario, with different assumptions about the maximally exposed individual, their age, and the amounts of air, water, soil, and foods they consume. For each exposure pathway one can compute the ratio between the exposure assumptions for any two scenarios. The product of the ratios comprises a Vulnerability Index. The index is higher for children than adults. For Washington this Index is reflected in the 'industrial' vs 'unrestricted' soil cleanup levels, which are 43.7 times lower for 'unrestricted'. This paper explores the similarities and differences in the exposure scenarios and vulnerability of the maximally exposed individuals and the consequences of a mismatch between current cleanup levels and possible future land uses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Application of Structured Decision Making to Hanford Site Radiological Air Monitoring - 17924

Radiological air monitoring is a component of an Environmental Surveillance (ES) program that has been in operation at the Department of Energy Hanford Site for several decades. The primary objectives of the ES program are protection of human health and the environment (on and off-site) as well as regulatory compliance. The ES program was designed decades ago when the plutonium-production reactors and related facilities at the Hanford Site were operational and air emissions were more widespread and significant than today. We employed a structured decision making (SDM) approach that integrates science with values and preferences to a Hanford Site air monitoring program decision. Specifically, a decision was necessary pertaining to the possible replacement of three air monitoring stations located in the 100 Area of the Hanford Site because the power line that supports these stations was near the end of its lifecycle. Although focused on this specific decision, the SDM model is more broadly applicable to decisions pertaining to adapting the air monitoring network to current Hanford operations. The value focused thinking approach that underlies SDM facilitates transparent and defensible decision making, and aids in communicating monitoring rationale. Some of the fundamental objectives elicited from the decision makers regarding management options for the three air monitoring stations included maximizing the ability to measure releases, minimizing environmental impacts, and maximizing social and economic sustainability. The fundamental objectives were linked to six objectives that could be measured (quantified) to allow a decision-analytic solution to the decision problem. Value functions and preference weights were developed for each of the objectives measures based on information obtained during a project workshop as well as by review and analysis of environmental data. Lastly, a set of five management options was identified that might achieve at least one of the objectives. A Bayes Network was developed as a solution to the decision problem pertaining to the three air stations (the 3 air stations decision). The Bayes Network describes the decision model graphically, and also serves as the computational engine for the decision analysis. The Bayes Network defines the relationship among the five management options and six objectives measures. In addition to the weights and value functions noted above, key inputs to the Bayes Network include a set of probabilities related to the different model states defined by the network. These include the probability of a significant release occurring, the probability that a release would be detected under each of the five management options, and the probability of achieving the other objective measures under each management option. In this manner the Bayesian Network captures the uncertainty in the components of the decision model. Replacing the three air monitoring stations with thermoluminescent dosimeters was identified as the preferred management option. A brief report was developed documenting the SDM model, including the workshop notes and analyses that were used to develop the objectives and model input variable values. This application demonstrates SDM's utility for supporting monitoring program decisions and, critically, providing a transparent and traceable basis for the decision. This relatively simple SDM model also provides a basis for an SDM model for monitoring decisions related to the more complex and holistic goal of achieving ES program objectives. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Managing work flow and logistic at waste processing facilities using the waste compliance and tracking system - 15392

Work flow and logistics at a busy radioactive waste processing complex or permitted treatment, storage, and disposal facility (TSDF) can pose a monumental challenge. An efficient operation requires good communication between engineering, logistics, and waste operators. The Los Alamos National Laboratory (LANL) has implemented an application that facilitates seamless communication of work flow requirements, between engineering, logistics, and waste operations personnel in the field. The Waste Compliance and Tracking System (WCATS), a comprehensive waste management system designed at LANL, provides four key elements to support logistics: (a) the container work path, (b) directed unit operation requests, (c) notification of pending operations, and (d) real-time status tools for office and field workers. The combination of these elements allows everyone to function as a team, with a shared knowledge of what is needed to accomplish facility objectives. The first element is like a road map indicating which unit operations are needed and in what sequence they should be performed; this is referred to as a 'work path'. It automatically routes a waste item or container from operation to operation. For example, a given work path might indicate that waste items require radiological survey, radioassay, and a technical review, in that order. When the work path is assigned to a container, the system enforces the correct order of operations. Directed unit operation 'requests', the second element, fills a gap between pre-planned, formal 'work path' activities and the need for flexibility to direct preparatory operations or deal with unexpected issues, like staging or mining containers in preparation for a shipment or transferring containers from one storage unit to another to clear a path for building maintenance. Logistics engineers prepare these 'requests', and the system monitors the status and completion of the work. The third element, notifications, allows team members to subscribe to and receive notice that an operation is pending, initiated, or complete. This functionality supports a range of communication options, including e-mail, cell phone, pager, or application in-box messaging. Notifications allow waste operations personnel to multi-task, and remain in the loop on the status of facility-wide activities. Finally, the fourth element provides tools that communicate work path pending operations and directed requests to field workers on their mobile computer, allowing them to mine or pick containers from storage units, and leverage the capabilities of a bar-code scanner to avoid selection mistakes. Oversight and summary tools are provided, allowing logistics personnel to monitor work path and request task status, identify work-flow bottlenecks, and maximize the efficiency of waste operations. The Waste Compliance and Tracking System (WCATS) provides an innovative, comprehensive set of tools that allow large-scale radioactive waste processing facilities to manage logistics, maximize efficient use of the workforce, and create a team environment, where everyone from management to the waste handlers have an understanding of the work load and what needs to be accomplished. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Nuclear aircraft carrier inactivation - Execution of waste management initiatives - 15565

After 6 years of planning efforts, in June 2013, Newport News Shipbuilding (NNS) began the execution phase of the inactivation of the USS Enterprise. The USS Enterprise decommissioning involves implementation of a new approach to defueling aircraft carriers, utilizing new processes for defueling and shipment of spent nuclear fuel and waste. During planning for this complex endeavor, NNS developed several process improvement initiatives including streamlining waste management processes and technology insertion using modeling and simulation (M and S) capabilities. One of the new approaches involves the establishment of a Waste Packaging Area (WPA) onboard the ship. The process assists with maximizing waste loading and shipments directly from the ship. Another waste management initiative includes the NNS/ Waste Vendor teaming effort to facilitate more efficient loading and shipment of inactivation waste. With execution underway, these initiatives are being put to the test to see if they can withstand the rigors of day-to-day production. NNS has implemented the use of the Modeling and Simulation (M and S) technology. During the planning phase, the M and S 3D Spatial Arrangement Tool was utilized to determine the optimal equipment layout within the new M-290 facility used for spent fuel packaging and ship-out and to determine the appropriate shipping container placement on the ship to maximize waste loading. The M and S technology proved to be a beneficial application resulting in continued utilization through the execution phase of the carrier inactivation. NNS is currently expanding the M-290 Facility Model to provide a visual representation of the facility, its processes, resources, and variable parameters that can be utilized as a decision support tool through simulation of the spent fuel packaging and ship-out process through the facility's life-cycle. NNS is also expanding the application of the waste management model to effectively predict waste forecast. The simulation model is linked with the defueling schedule which captures the operational elements of the waste flow process. The model extrapolates the data to provide waste generation output to assess the most efficient and cost effective path for radiological waste shipments offsite. The ability to conduct waste forecasting allows streamlining of the waste management process in support of complex defueling operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Final Closure of the Maxey Flats Low-Level Radioactive Waste Disposal Site - 16088

This paper describes the final closure remedy for the former Maxey Flats Low-Level Radioactive Waste Disposal Site (MFDS), the challenges presented at the site due to the condition of the disposal facility and waste, and their resolution through comprehensive geo-synthetic design. The MFDS is an inactive landfill located in Kentucky on a ridge surrounded by a buffer zone. Historically, waste disposal occurred without reducing voids or without compacting the placed waste. Settlement and water management issues led to releases of radioactive contamination into surrounding waters, resulting in the closure of the facility in 1977. The final closure remedy consists of 1) development and implementation oversight of a sump abandonment design to ensure no direct pathways for infiltrating water to contact the waste and 2) development and implementation oversight of the Final Closure Period (FCP) cap design. Challenges successfully addressed by the FCP scope included: Abandon sumps to minimize storm water migrating into the waste; Address potential existing groundwater waste interaction; Maximum use of on-site cap construction materials; Design cap to fit very restricted site footprint; Assess and address potential isolated differential settlement; Maximize passive storm water management; Provide alternative site access during construction. The FCP remedy and resultant design satisfies these challenges through use of layers of geo-grid-reinforced soil and geo-synthetic materials, contours and slopes that minimize the quantities of construction materials while maximizing the use of available material, probabilistic subsidence modeling, an integrated storm water management system ensuring the slow release of storm water into receiving streams, and a dedicated construction haul road system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Strategic Planning and Decisions Tools to Enhance EM Mission Execution - 16552

Maximizing the success of an organization depends on many things with a key one being the focus and quality of the management decisions made by the organisation's senior leadership team. Successfully advancing an organisation's agenda requires operational, tactical, and strategic decisions. These decisions involve both decisions on specific actions, as well as decisions about planning. In addition to the day-to-day decisions of running the business, the leadership team should be allocating appropriate time toward developing organizational strategic objectives. Strategic planning is an organisation's process of defining its direction and strategies, and plotting how to accomplish those strategies. Strategic planning is essential to the long term viability of the organization. The pathway to success with strategic planning is not nearly so obvious and straight forward as with operational decisions. Organizational leaders must resist the temptation to minimize the time allocated to strategic thinking and strategic planning. Strategic thinking and strategic planning are centered around making sure that your organization is doing the right things, instead of just doing things right. Management guru Peter Drucker noted that 'There is nothing more wasteful than becoming highly efficient at doing the wrong things'. Strategic thinking is used in deciding what to do. Tactical thinking is used in deciding how to do it. Decision tools can be utilized to improve the results of the strategic planning process. In certain situations, properly selected decision tools will provide a mechanism or a process for making better decisions, or for channeling strategic thought and strategic planning toward enlightened alternative approaches. Decision tools can also provide for assigning a quantitative measure of merit or goodness, or at least a semi-quantitative measure of merit to multiple decision options. Properly selected and utilized, decision tools provide the leadership team with additional insight into the consequences of their decisions. Appropriately selected decision tools can be utilized to maximize the effectiveness of your strategic planning efforts. Decision tools can be used to quantify strategic decision options within a particular framework, providing insights into alternatives to improve an organisation's most effective execution of the DOE EM clean up mission. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Evaluation of Potential Dose to Off-site Receptors from On-site Removable Contamination - 18521

Calculations used in making corrective action decisions estimate the maximum potential dose to on-site receptors exposed to contamination from nuclear testing activities at U.S. Department of Energy, Environmental Management Nevada Program Soils Activity release sites. At many of these release sites, removable contamination is present at levels that require controls to be in place under Title 10 Code of Federal Regulations Part 835, 'Occupational Radiation Protection.' When significant levels of removable contamination are present at a release site, it may be necessary to evaluate the potential dose to off-site receptors from removable contamination that has the potential to be transported off the contaminated site. The protocols described herein could be used to evaluate the potential dose to off-site receptors to ensure that corrective action decisions consider both on-site and off-site potential receptors. The calculation of estimated dose to a receptor can be accomplished by establishing a scenario that describes the exposure (e.g., time and pathway) of the individual to the radiological contamination and by using the properties of the contaminants (e.g., dose conversion factors). Radiological contamination transported from the site has the potential to expose off-site receptors under a potentially large number of exposure scenarios that cannot be comprehensively defined. However, a scenario was developed to represent a maximally exposed off-site receptor. Because the estimated dose to the maximally exposed off-site receptor based on maximum post-closure release site activity levels is less than the on-site dose decision level, corrective action decisions at the Nevada National Security Site Soils Activity release sites are also protective of potential off-site receptors when significant levels of removable contamination are present. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Preliminary Conceptual Neutronic, Thermal, and Mechanical Design for {sup 238}Pu ATR Targets

Pu-238 is a valuable heat source material used to manufacture radioisotope power systems (RPSs), which are needed to provide electrical power for space exploration and other missions. Before 1989, the United States Department of Energy (DOE) produced Pu-238 at the Savannah River Site in South Carolina in nuclear reactors that are now decommissioned. From 1989 through 2009, existing DOE inventories of Pu- 238 were supplemented by quantities of Pu-238 purchased from Russia; however, supplies available for purchase from Russia are limited. DOE has restored domestic production to meet future demand; otherwise, NASA will be in danger of not being able to use RPSs in future missions. The Pu-238 Supply Program has the objective of reestablishing the domestic capability for producing Pu-238. In order to meet the quantities of Pu-238 needed to support NASA space mission and other federal users the ATR is being considered as an important asset to achieve the desired production of the radioisotope. In order to determine the constraints and parameters needed to maximize the production of Pu-238 at ATR a preliminary conceptual design target design was performed. The preliminary conceptual design had two principal goals: 1. Perform a trade study to determine an ATR target length that maximizes production as well as minimize the need to modify ORNL's target. 2. Evaluate the selected preliminary design from the standpoint of the ATR nuclear safety basis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Value of Information in Fuel Cycle Decision-making

Transitions between nuclear fuel cycles with uncertain key parameters (e.g., SNF and HLW disposal costs, fast reactor capital costs) have been examined using a decision-making under uncertainty methodology. The methodology explicitly incorporates uncertainties in key parameters into the decision-making process by constructing a stochastic model and embedding uncertainties as bifurcations in the decision-tree. The framework of this methodology allows for interpretation using a real options valuation or game theoretic approach, reviewed in. The work presented here extends the decision-making under uncertainty framework to calculate the value of information, which may be used to inform a game against nature. These games against nature have been applied to resource allocation problems, where scarce resources are allocated to maximize expected payoffs. More broadly, the value of developing alternative technologies may be considered under the same framework, where an investment portfolio for technology deployment may be developed. Here, the value of information is taken as the value of reducing uncertainty in key parameters, and these values may be substituted for the traditional payoff matrix when considering allocating scarce resources. Games against nature may provide a unique perspective on R and D funding decisions when considering transitions between nuclear fuel cycles. By determining the value of reducing uncertainties (of gaining information on probability distributions) scarce resources may be allocated in such a way to maximize their utility. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Session 058 - Panel: Ensuring Strong Return on Investment for DOE EM Technology Development: DOE Views (1/2) (R1.26)

The panel represented the views of US DOE National Laboratories and DOE Contractors and focused on DOE Technology Development Projects discussing how they approach tech development to maximize return on investment. Successful examples were discussed. Panelists with presentations: Ensuring a Strong ROI for DOE EM Technology Development (Jud Virden); The DOE EM Technology Development Technical Assistance Program (Carol Eddy-Dilek); SRR Liquid Waste Technology Development Program: Encouraging Creativity Maximize Return on Investment (Vijay Jain); Ensuring Strong Return on Investment for DOE EM Technology Development: A Vendor Perspective (Martin Williams)

99 GENERAL AND MISCELLANEOUS↗