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Various embodiments described in this disclosure relate to methods and computer-based systems that implement those methods for converting tasks performed as part of a procedure into dynamic procedure tasks. Such dynamic procedure tasks may be used by computer-based procedure solutions to create highly dynamic computer-based procedures.
A method for increasing a speed or energy efficiency at which a computer is capable of modeling a plurality of random walkers. The method includes defining a virtual space in which a plurality of virtual random walkers will move among different locations in the virtual space, wherein the virtual space comprises a plurality of vertices and wherein the different locations are ones of the plurality of vertices. A corresponding set of neurons in a spiking neural network is assigned to a corresponding vertex such that there is a correspondence between sets of neurons and the plurality of vertices, wherein a spiking neural network comprising a plurality of sets of spiking neurons is established. A virtual random walk of the plurality of virtual random walkers is executed using the spiking neural network, wherein executing includes tracking how many virtual random walkers are at each vertex at a given time increment.
A method of recovering an elemental rare earth metal comprises placing a rare earth-containing material comprising a rare earth metal in a reaction solution comprising a reducing agent and a non-aqueous solvent comprising an ionic liquid or a eutectic mixture, reducing the rare earth metal with the reducing agent to form a metallic rare earth metal and cations of the reducing agent, transferring the cations of the reducing agent from the reaction solution to an electrochemical cell through an ion exchange membrane, and reducing the cations of the reducing agent in the electrochemical cell. Related methods of forming an elemental rare earth metal, and related systems are disclosed.
A method of forming at least a component of a heat exchanger comprises introducing a feed material comprising a first portion including a matrix material and a second portion including a sacrificial material on a surface of a substrate, exposing at least the first portion to energy to form bonds between particles of the matrix material and form a first thickness of a structure, introducing additional feed material comprising the first portion over the first thickness of the structure, exposing the additional feed material to energy to form a second thickness of the structure, and removing the sacrificial material from the structure to form at least one channel in the structure. Related heat exchangers and components, and related methods are disclosed.
The present invention relates to catalysts, methods of making catalysts, and methods of using catalysts, where the catalysts include: at least one of a transition metal and a transition metal oxide supported by yttria-stabilized zirconia (YSZ), where the transition metal is promoted by at least one of an alkali metal and an alkaline-earth metal.
Multiple rocket engine exhaust plumes calculated by method of characteristics and finite difference and compared with schlieren data
This corrigendum clarifies the conditions under which the proof of convergence of Theorem 1 from the original article is valid. We erroneously stated as one of the conditions for the Schwarz alternating method to converge that the energy functional be strictly convex for the solid mechanics problem. Finally, we have relaxed that assumption and changed the corresponding parts of the text. None of the results or other parts of the original article are affected.
We study a multigrid method for solving large linear systems of equations with tensor product structure here. Such systems are obtained from stochastic finite element discretization of stochastic partial differential equations such as the steady-state diffusion problem with random coefficients. When the variance in the problem is not too large, the solution can be well approximated by a low-rank object. In the proposed multigrid algorithm, the matrix iterates are truncated to low rank to reduce memory requirements and computational effort. The technique is proved convergent with an analytic error bound. Numerical experiments show its effectiveness in solving the Galerkin systems compared to the original multigrid solver, especially when the number of degrees of freedom associated with the spatial discretization is large.
This Commercial and Industrial Lighting Controls Evaluation Protocol (the protocol) describes methods to account for energy savings resulting from programmatic installation of lighting control equipment in large populations of commercial, industrial, government, institutional, and other nonresidential facilities. This protocol does not address savings resulting from changes in codes and standards, or from education and training activities. When lighting controls are installed in conjunction with a lighting retrofit project, the lighting control savings must be calculated parametrically with the lighting retrofit project so savings are not double counted.
Addressing other evaluation issues that have been raised in the context of energy efficiency programs, this chapter focuses on methods used to address the persistence of energy savings, which is an important input to the benefit/cost analysis of energy efficiency programs and portfolios. In addition to discussing 'persistence' (which refers to the stream of benefits over time from an energy efficiency measure or program), this chapter provides a summary treatment of these issues -Synergies across programs -Rebound -Dual baselines -Errors in variables (the measurement and/or accuracy of input variables to the evaluation).
Evaluating an energy efficiency program requires assessing the total energy and demand saved through all of the energy efficiency measures provided by the program. For large programs, the direct assessment of savings for each participant would be cost-prohibitive. Even if a program is small enough that a full census could be managed, such an undertaking would almost always be an inefficient use of evaluation resources. The bulk of this chapter describes methods for minimizing and quantifying sampling error. Measurement error and regression error are discussed in various contexts in other chapters.
This chapter presents an overview of best practices for designing and executing survey research to estimate gross energy savings in energy efficiency evaluations. A detailed description of the specific techniques and strategies for designing questions, implementing a survey, and analyzing and reporting the survey procedures and results is beyond the scope of this chapter. So for each topic covered below, readers are encouraged to consult articles and books cited in References, as well as other sources that cover the specific topics in greater depth. This chapter focuses on the use of survey methods to collect data for estimating gross savings from energy efficiency programs.
Estimated energy savings are calculated as the difference between the energy use during the baseline period and the energy use during the post installation period of the EEM. This chapter describes the physical properties measured in the process of evaluating EEMs and the specific metering methods for several types of measurements. Skill-level requirements and other operating considerations are discussed, including where, when, and how often measurements should be made. The subsequent section identifies metering equipment types and their respective measurement accuracies. This is followed by sections containing suggestions regarding proper data handling procedures and the categorization and definition of several load types.
This protocol is intended to describe the recommended method when evaluating the whole-building performance of new construction projects in the commercial sector. The protocol focuses on energy conservation measures (ECMs) or packages of measures where evaluators can analyze impacts using building simulation. These ECMs typically require the use of calibrated building simulations under Option D of the International Performance Measurement and Verification Protocol (IPMVP).
Savings from electric energy efficiency measures and programs are often expressed in terms of annual energy and presented as kilowatt-hours per year (kWh/year). However, for a full assessment of the value of these savings, it is usually necessary to consider the measure or program's impact on peak demand as well as time-differentiated energy savings. This cross-cutting protocol describes methods for estimating the peak demand and time-differentiated energy impacts of measures implemented through energy efficiency programs.
This is the complete set of Uniform Methods Project protocols for determining energy efficiency savings for specific measures, all within one report. The report includes the following chapters: Chapter 1: Introduction. Chapter 2: Commercial and Industrial Lighting Evaluation Protocol. Chapter 3: Commercial and Industrial Lighting Controls Evaluation Protocol. Chapter 4: Small Commercial and Residential Unitary and Split System HVAC Cooling Equipment-Efficiency Upgrade Evaluation Protocol. Chapter 5: Residential Furnaces and Boilers Evaluation Protocol. Chapter 6: Residential Lighting Evaluation Protocol. Chapter 7: Refrigerator Recycling Evaluation Protocol. Chapter 8: Whole-Building Retrofit with Consumption Data Analysis Evaluation Protocol. Chapter 9: Metering Cross-Cutting Protocol. Chapter 10: Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocol. Chapter 11: Sample Design Cross-Cutting Protocol. Chapter 12: Survey Design and Implementation for Estimating Gross Savings Cross-Cutting Protocol. Chapter 13: Assessing Persistence and Other Evaluation Issues Cross-Cutting Protocol. Chapter 14: Chiller Evaluation Protocol. Chapter 15: Commercial New Construction Evaluation Protocol. Chapter 16: Retrocommissioning Evaluation Protocol. Chapter 17: Residential Behavior Evaluation Protocol. Chapter 18: Variable Frequency Drive Evaluation Protocol. Chapter 19: HVAC Controls (DDC/EMS/BAS) Evaluation Protocol. Chapter 20: Data. Center IT Efficiency Measures Evaluation Protocol. Chapter 21: Estimating Net Savings - Common Practices. Chapter 22: Compressed Air Evaluation Protocol. Chapter 23: Combined Heat and Power Evaluation Protocol. Chapter 24: Strategic Energy Management (SEM) Evaluation Protocol
This document has been updated in August 2020. This document was developed for the U.S. Department of Energy Uniform Methods Project (UMP). The UMP provides model protocols for determining energy and demand savings that result from specific energy-efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The protocols are updated on an as-needed basis. The UMP protocols can be used by utilities, program administrators, public utility commissions,evaluators, and other stakeholders for both program planning and evaluation. To learn more about the UMP, visit the website, https://energy.gov/eere/about-us/ump-home, or download the UMP introduction document at http://www.nrel.gov/docs/fy17osti/68557.pdf.