Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Cost optimization”

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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

COMPASS Final Report: Radioisotope Electric Propulsion (REP) Centaur Orbiter New Frontiers Mission

Radioisotope Electric Propulsion (REP) has been shown in past studies to enable missions to outer planetary bodies including the orbiting of Centaur asteroids. Key to the feasibility for REP missions are long life, low power electric propulsion (EP) devices, low mass Radioisotope Power System (RPS) and light spacecraft (S/C) components. In order to determine the key parameters for EP devices to perform these REP missions a design study was completed to design an REP S/C to orbit a Centaur in a New Frontiers (NF) cost cap. The design shows that an orbiter using several long lived (approx.200 kg xenon (Xe) throughput), low power (approx.700 W) Hall thrusters teamed with six (150 W each) Advanced Stirling Radioisotope Generators (ASRG) can deliver 60 kg of science instruments to a Centaur in 10 yr within the NF cost cap. Optimal specific impulses (Isp) for the Hall thrusters were found to be around 2000 s with thruster efficiencies over 40 percent. Not only can the REP S/C enable orbiting a Centaur (when compared to an all chemical mission only capable of flybys) but the additional power from the REP system can be used to enhance science and simplify communications. The mission design detailed in this report is a Radioisotope Power System (RPS) powered EP science orbiter to the Centaur Thereus with arrival 10 yr after launch, ending in a 1 yr science mapping mission. Along the trajectory, approximately 1.5 yr into the mission, the REP S/C does a flyby of the Trojan asteroid Tlepolemus. The total (Delta)V of the trajectory is 8.9 km/s. The REP S/C is delivered to orbit on an Atlas 551 class launch vehicle with a Star 48 B solid rocket stage

Oleson, Steven R.↗
NASA NTRS2013

Practical Application of PRA as an Integrated Design Tool for Space Systems

This paper presents the application of the first comprehensive Probabilistic Risk Assessment (PRA) during the design phase of a joint NASA/NOAA weather satellite program, Geostationary Operational Environmental Satellite Series R (GOES-R). GOES-R is the next generation weather satellite primarily to help understand the weather and help save human lives. PRA has been used at NASA for Human Space Flight for many years. PRA was initially adopted and implemented in the operational phase of manned space flight programs and more recently for the next generation human space systems. Since its first use at NASA, PRA has become recognized throughout the Agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success throughout project lifecycles. PRA is now included as a requirement during the design phase of both NASA next generation manned space vehicles as well as for high priority robotic missions. The influence of PRA on GOES-R design and operation concepts are discussed in detail. The GOES-R PRA is unique at NASA for its early implementation. It also represents a pioneering effort to integrate risks from both Spacecraft (SC) and Ground Segment (GS) to fully assess the probability of achieving mission objectives. PRA analysts were actively involved in system engineering and design engineering to ensure that a comprehensive set of technical risks were correctly identified and properly understood from a design and operations perspective. The analysis included an assessment of SC hardware and software, SC fault management system, GS hardware and software, common cause failures, human error, natural hazards, solar weather and infrastructure (such as network and telecommunications failures, fire). PRA findings directly resulted in design changes to reduce SC risk from micro-meteoroids. PRA results also led to design changes in several SC subsystems, e.g. propulsion, guidance, navigation and control (GNC), communications, mechanisms, and command and data handling (C&DH). The fault tree approach assisted in the development of the fault management system design. Human error analysis, which examined human response to failure, indicated areas where automation could reduce the overall probability of gaps in operation by half. In addition, the PRA brought to light many potential root causes of system disruptions, including earthquakes, inclement weather, solar storms, blackouts and other extreme conditions not considered in the typical reliability and availability analyses. Ultimately the PRA served to identify potential failures that, when mitigated, resulted in a more robust design, as well as to influence the program's concept of operations. The early and active integration of PRA with system and design engineering provided a well-managed approach for risk assessment that increased reliability and availability, optimized lifecyc1e costs, and unified the SC and GS developments.

Kalia, Prince↗
NASA NTRSDate not supplied

Impact of Analytic Derivatives on Optimization of N-Impulse Orbit Transfer

Several formulations are possible for the optimization of N-impulse two-body orbit transfers. One formulation that assumes the firstN−1impulses are design variables and implements Lambert’s algorithm in the final leg is here considered. This paper presents a derivation for the analytic expressions of the gradients needed to optimize this formulation. The impact of using these analytic expressions on the optimization computational cost is also presented. A linear system of equations is developed that approximates the Lambert’s problem solution in a way that is suitable for computing the analytic gradients. The derivations of the analytic gradients, as well as numerical case studies for 2-impulse and 3-impulse orbit transfers, are presented. The numerical case studies highlights a significant reduction in the computational cost, measured in terms of the number of function calls.

Ahmed Ellithy↗
DOE OSTI2020

Combined Heat and Power Technology Fact Sheet Series: Thermal Energy Storage

This fact sheet provides an overview of thermal energy storage (TES) technologies, which heat or cool a storage medium and, when needed, deliver the stored thermal energy to meet heating or cooling needs. TES systems are used in commercial buildings, industrial processes, and district energy installations to deliver stored thermal energy during peak demand periods, thereby reducing peak energy use. TES systems are often integrated with electric or absorption chillers to reduce peak electricity costs and, in the case of new construction, to reduce capital costs by optimizing chiller size. TES technologies can support sites that have either renewable or fossil power generation, including combined heat and power (CHP) installations. With CHP, TES can help optimize equipment size by reducing the required peak CHP thermal capacity and increasing annual CHP usage. TES can also provide turbine inlet cooling for gas turbines used in CHP applications, which increases power production in hot ambient conditions.

Combined Heat and Power, CHP, Thermal Energy, Tech↗
DOE OSTI2020

BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data

We describe the BeyondPlanck project in terms of motivation, methodology and main products, and provide a guide to a set of companion papers that describe each result in fuller detail. Building directly on experience from ESA's Planck mission, we implement a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations. The primary product is a joint posterior distribution P(omega|d), where omega represents the set of all free instrumental (gain, correlated noise, bandpass etc.), astrophysical (synchrotron, free-free, thermal dust emission etc.), and cosmological (CMB map, power spectrum etc.) parameters. Some notable advantages of this approach are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. As a practical demonstration of this framework, we focus in particular on low-l CMB polarization reconstruction, paying special attention to the LFI 44 GHz channel. We find evidence of significant residual systematic effects that are still not accounted for in the current processing, but must be addressed in future work. These include a break-down of the 1/f correlated noise model at 30 and 44 GHz, and scan-aligned stripes in the Southern Galactic hemisphere at 44 GHz. On the Northern hemisphere, however, we find that all results are consistent with the LCDM model, and we constrain the reionization optical depth to tau = 0.067 +/- 0.016, with a low-resolution chi-squared probability-to-exceed of 16%. The marginal CMB dipole amplitude is 3359.5 +/- 1.9 uK. (Abridged.)

Andersen, KJ↗
DOE OSTI2022

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

Five contemporary technologies are discussed in the context of their potential roles in particle tracking for future high energy physics applications. These include sensors of the 3D configuration, in both diamond and silicon, submicron-dimension pixels, thin film detectors, and scintillating quantum dots in gallium arsenide. Drivers of the technologies include radiation hardness, excellent position, vertex, and timing resolution, simplified integration, and optimized power, cost, and material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. Here, the effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. The effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2023

Hybrid Energy System to H2 to Green Steel/Ammonia

Green hydrogen is a vital pathway to decarbonize industrial sectors responsible for the largest portion of greenhouse gas emissions, including ammonia/fertilizer and steel. It takes approximately a GW-scale renewables hybrid-H2 system to fully convert one average U.S. steel plant to a green steel plant, with an annual production capacity of 100 million metric tons per year. The optimized cost-effective operation of renewables-H2 plants are highly dependent on location and the specific end use designs. This project focused on the analysis of GW-scale off-grid, tightly-coupled, co-located systems to reduce overall cost compared with steam methane reform with and without carbon capture and grid connected systems (see Figure 1).

ammonia↗
DOE OSTI2024

Streaming in a Nuclear Grade Sandwich Composite for Microreactor Shielding

The NGSC is a new approach to develop a shield structure for microreactors which combines the biological shielding with the reactor pressure vessel. Six layers of SS316 skins and core materials are present in the NGSC, where the core materials are reduce the neutron and gamma dose. Previous work has examined how a simplified NGSC can be optimized for cost, dose, and weight. This work explored the inclusion of SS36 ribs, which helps maintain the structural integrity of the NGSC, affects the transportation of radiation through the NGSC. For B$_4$C layers, the addition of ribs reduces neutron absorption but increase photon absorption. For WB$_4$-cermet layers, the addition of ribs reduces neutron absorption and reduces photon absorption.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Best Practices for Smart Grid-Interactive Efficient Building Ready Performance Contracts

Grid-interactive efficient building (GEB) measures reduce costs and optimize energy use for additional grid services by coordinating building energy loads and providing continuous demand management. Incorporating GEB energy conservation measures (ECMs) in performance contracts is reliant upon multiple factors. These factors include site selection with utility tariffs and incentives favorable to GEB, the identification of GEB as a priority in the initial stages of the contracting process, integration of GEB within comprehensive performance contracts with multiple other ECMs, and careful consideration of GEB measurement and verification (M&V) for energy savings performance contracts (ESPCs) and performance assurance for utility energy service contracts (UESCs).

building energy loads↗
DOE OSTI2024

A Primer on Using Analysis to Guide Plastic Circularity

BOTTLE, funded by DOE's Advanced Materials & Manufacturing Technologies Office and Bioenergy Technologies Office (BETO), conducts analysis-guided R&D to change the way we recycle plastics. But what does analysis really mean? In this webinar, BOTTLE Analysis Co-Lead Dr. Taylor Uekert, a researcher with the National Renewable Energy Laboratory (NREL), will introduce key analysis techniques such as techno-economic analysis, life cycle assessment, and environmental justice evaluation. Relevant to both analysts and non-analysts, Dr. Uekert will cover the basics of analysis techniques and discuss how these methods are conducted and interpreted. She will provide examples from the BOTTLE portfolio demonstrating their use in benchmarking and optimizing the costs and environmental impacts of new innovations in plastic redesign and recycling. If you are working in the plastics recycling field - from experimental work to analysis to community-focused projects - you won't want to miss this talk. The webinar will end with a Q&A session.

analysis↗
NASA NTRS2018

Preliminary Design of the Superconducting Rotor for NASA's High-Efficiency Megawatt Motor

NASA Glenn Research Center is developing a 1.4~MW high-efficiency electric machine for future electrified aircraft to reduce energy consumption, emissions, and noise. This wound-field, synchronous machine employs a self-cooled, superconducting rotor to achieve excellent specific power and efficiency. The design of the superconducting rotor and the optimization of its electromagnetic and structural responses are analyzed in this paper. Candidate designs are evaluated in terms of absolute performance, specific performance, and performance per cost. It is found that optimizing the electromagnetic response for absolute or specific performance yields designs that are similar to each other, but opposite of the cost-optimized design. A method to define the thermal requirements of the superconducting coils and integrated cryocooler is also presented.

electric machines↗
NASA NTRS2018

Preliminary Design of the Superconducting Rotor for NASA's High-Efficiency Megawatt Motor

NASA Glenn Research Center is developing a 1.4 MW high-efficiency electric machine for future electrified aircraft to reduce energy consumption, emissions, and noise. This wound-field, synchronous machine employs a self-cooled, superconducting rotor to achieve excellent specific power and efficiency. The design of the superconducting rotor and the optimization of its electromagnetic and structural responses are analyzed in this paper. Candidate designs are evaluated in terms of absolute performance, specific performance, and performance per cost. It is found that optimizing the electromagnetic response for absolute or specific performance yields designs that are similar to each other, but opposite of the cost-optimized design. A method to define the thermal requirements of the superconducting coils and integrated cryocooler is also presented.

Scheidler, Justin↗
DOE OSTI2024

Gains in operational flexibility, safety margins, and cost efficiencies via integrated Plant Reload Optimization platform

The U.S. Department of Energy Light Water Reactor Sustainability Program Risk-Informed Systems Analysis Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimizing core design. Optimizing the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible core configuration options, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization platform, which supports artificial-intelligence-based reactor core designing, is now fully capable of handling realistic problems. The Plant ReLoad Optimization platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual ENvironment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multiobjective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗