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 1,387 records · Page 77

A comprehensive methodology for intelligent systems life-cycle cost modelling

As NASA moves into the last part on the twentieth century, the desire to do 'business as usual' has been replaced with the mantra 'faster, cheaper, better'. Recently, new work has been done to show how the implementation of advanced technologies, such as intelligent systems, will impact the cost of a system design or in the operational cost for a spacecraft mission. The impact of the degree of autonomous or intelligent systems and human participation on a given program is manifested most significantly during the program operational phases, while the decision of who performs what tasks, and how much automation is incorporated into the system are all made during the design and development phases. Employing intelligent systems and automation is not an either/or question, but one of degree. The question is what level of automation and autonomy will provide the optimal trade-off between performance and cost. Conventional costing methodologies, however, are unable to show the significance of technologies like these in terms of traceable cost benefits and reductions in the various phases of the spacecraft's lifecycle. The proposed comprehensive life-cycle methodology can address intelligent system technologies as well as others that impact human-machine operational modes.

Korsmeyer, David J.↗

The Pegasus air-launched space booster payload interfaces and processing procedures for small optical payloads

Pegasus and the PegaStar integrated spacecraft bus are described, and an overview of integration and launch operations is provided. Payload design issues include payload volume and mass capability, payload interfaces, and design loads. Vehicle and payload processing issues include integration and handling methods, facilities, contamination control, and launch operations. It is noted that Pegasus provides small satellite users with a cost-effective means for delivering payloads into the specific orbits at the optimal time to meet the most demanding mission requirements. PegaStar provides a flexible cost-effective means for providing long-term on-orbit support while minimizing total program risk and cost.

Mosier, Marty↗

Excited State Orbital Optimization via Minimizing the Square of the Gradient: General Approach and Application to Singly and Doubly Excited States via Density Functional Theory

We present a general approach to converge excited state solutions to any quantum chemistry orbital optimization process, without the risk of variational collapse. The resulting square gradient minimization (SGM) approach only requires analytic energy/Lagrangian orbital gradients and merely costs 3 times as much as ground state orbital optimization (per iteration), when implemented via a finite difference approach. SGM is applied to both single determinant ΔSCF and spin-purified restricted open-shell Kohn-Sham (ROKS) approaches to study the accuracy of orbital optimized DFT excited states. It is found that SGM can converge challenging states where the maximum overlap method (MOM) or analogues either collapse to the ground state or fail to converge. We also report that ΔSCF/ROKS predict highly accurate excitation energies for doubly excited states (which are inaccessible via TDDFT). Singly excited states obtained via ROKS are also found to be quite accurate, especially for Rydberg states that frustrate (semi)local TDDFT. Our results suggest that orbital optimized excited state DFT methods can be used to push past the limitations of TDDFT to doubly excited, charge-transfer, or Rydberg states, making them a useful tool for the practical quantum chemist's toolbox for studying excited states in large systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimal aeroassisted coplanar orbital transfer using an energy model

The atmospheric portion of the trajectories for the aeroassisted coplanar orbit transfer was investigated. The equations of motion for the problem are expressed using reduced order model and total vehicle energy, kinetic plus potential, as the independent variable rather than time. The order reduction is achieved analytically without an approximation of the vehicle dynamics. In this model, the problem of coplanar orbit transfer is seen as one in which a given amount of energy must be transferred from the vehicle to the atmosphere during the trajectory without overheating the vehicle. An optimal control problem is posed where a linear combination of the integrated square of the heating rate and the vehicle drag is the cost function to be minimized. The necessary conditions for optimality are obtained. These result in a 4th order two-point-boundary-value problem. A parametric study of the optimal guidance trajectory in which the proportion of the heating rate term versus the drag varies is made. Simulations of the guidance trajectories are presented.

Halyo, Nesim↗

Dynamic Systems Analysis for Turbine Based Aero Propulsion Systems

The aircraft engine design process seeks to optimize the overall system-level performance, weight, and cost for a given concept. Steady-state simulations and data are used to identify trade-offs that should be balanced to optimize the system in a process known as systems analysis. These systems analysis simulations and data may not adequately capture the true performance trade-offs that exist during transient operation. Dynamic systems analysis provides the capability for assessing the dynamic tradeoffs at an earlier stage of the engine design process. The dynamic systems analysis concept, developed tools, and potential benefit are presented in this paper. To provide this capability, the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) was developed to provide the user with an estimate of the closed-loop performance (response time) and operability (high pressure compressor surge margin) for a given engine design and set of control design requirements. TTECTrA along with engine deterioration information, can be used to develop a more generic relationship between performance and operability that can impact the engine design constraints and potentially lead to a more efficient engine.

dynamic analysis↗

Future of Fuel Savings

Using automation to free up controllers for more strategic management of air traffic is one approach being studied by NASA as it seeks to boost airspace system capacity and efficiency, thereby saving fuel. Heinz Erzberger, a NASA Ames Research Center senior scientist, says the Advanced Airspace Concept (AAC) has been studied for several years. It could increase efficiency 15% by providing optimal routes that cut airlines direct operating costs. A 25% increase in landings on existing runways could follow an important benefit. AAC is one of the efforts to be reviewed by the Joint Planning and Development Organization, an FAA-led initiative by six federal agencies to redesign the U.S. air transportation system by 2025. The main goal is to triple air traffic capacity within 20 years to avert the sort of gridlock that would make fuel consumption only one of many travel nightmares. The automated system approach would allow aircraft to fly optimal trajectories. A trajectory would be defined in the standard three dimensions and eventually include the fourth, time. The management of air traffic by the data-linked exchange of trajectories would start at high altitude and eventually move down to lower altitudes. The automated concept is an outgrowth of the type of tools developed by NASA for use by FAA controllers in managing traffic flows over the years, including ones that optimize routings for the best fuel burn. But AAC would push automation further to reduce workload so controllers can focus on "solving strategic control problems, managing traffic flow during changing weather and ... other unusal events." One key component, the automated trajectory server (ATS), is a ground systems that would rely on software to manage flight path requests from aircrews and controllers. But, Erzberger acknowledges, "The FAA's current plan for upgrades to air traffic services does not include [allowing] the future ground system to issue separation-critical clearances of trajectory changes autonomously to aircraft via data link without explicit approval of a controller," as the AAC proposes. The AAC enables pilots or controllers to data link requests for a trajectory change to the ATS for approval after they are deconflicted with the paths of other aircraft. To divert around storms, for example, pilots could data link their trajectory preference to the ATS. Since several aircraft might request similar routes, the computer would then have to suggest alternatives. This could be accomplished without pilot-controller radio calls, a big bottleneck now. The ATS would have a built-in conflict monitor to call for a resolution (turn, climb or descend), when loss of separation is likely in 1-20 min. The AAC system would reduce controller errors by 90%, according to NASA Ames estimates. The AAC would have a back-up program to assure separation-Tactical Separation Assurance (TSAFE). It s designed to detect short-term traffic conflicts within 3-4 min. of loss of separation. The last line of defense would still be provided by traffic alert & collision avoidance systems (TCAS).

Hughes, David↗

Planning for a Resilient Home Electricity Supply System

Resilience of power systems is already a key issue that is getting frequent attention all over the world. It is useful to analyze resilience issues not only for bulk supply, but at all levels including at a customer level. This is because distributed energy resources can play a prominent role in enhancing resilience. Although the literature on planning models, tools and data for bulk supply and distribution systems have expanded in recent years, customer-centric planning, e.g., for an individual household, is yet to receive adequate attention. Although solar PV and battery storage at a household level have been analyzed, how these resources can be optimally combined, together with grid supply, from a resilience perspective is the focus of this study. The study demonstrates how a conceptual framework can be developed to show the trade-off between system costs and resilience including its dimensions such as duration, depth and frequency of service outages. A planning model is developed that incorporates multiple facets of resilience and individual customer preferences. The model considers power system resilience explicitly as a constraint. The model is implemented for a household level case study in Miami, Florida. The results show there are complex trade-offs among different dimensions of resilience. The study demonstrates how combined resilience metrics can be formulated and evaluated using the proposed least-cost planning model at a household level to optimize grid supply together with solar, battery storage and diesel generators. The model allows a planner to directly embed a resilience standard to drive the optimal supply mix. These concepts and the modeling construct can also be applied at other levels of planning, including community level and bulk supply system planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Design study of wind turbines 50 kW to 3000 kW for electric utility applications. Volume 1: Summary report

Wind turbine configurations that would lead to generation of electrical power in a cost effective manner were considered. All possible overall system configurationss, operating modes, and sybsystem concepts were evaluated for both technical feasibility and compatibility with utility networks, as well as for economic attractiveness. A design optimization computer code was developed to determine the cost sensitivity of the various design features, and thus establish the configuration and design conditions that would minimize the generated energy costs. The preliminary designs of both a 500 kW unit and a 1500 kW unit operating in a 12 mph and 18 mph median wind speed respectively, were developed. The rationale employed and the key findings are summarized.

Source record↗

Fundamental Experimental Tests and Modeling of LOX/CH4 Engines at High Pressures

In recent years, the space travel industry has grown exponentially, resulting in the need for a low-cost, efficient rocket engine fuel. As such, there has been renewed interest in utilizing liquid natural gas (LNG) as it is less likely to soot than kerosene-based fuels and has widespread availability and low cost of use as compared to the traditional RP-X and even liquid methane (LCH4) fuels due to the reduced need for refinement. However, current literature does not fully cover varying blends of natural gas and the effects that impurities have on natural gas/methane fuels, with most studies being confined to low-pressure applications. Therefore, new experimental ignition delay time measurements at rocket engine relevant pressures are essential to ensure current chemical kinetic models capture the ignition behavior at these elevated conditions and to determine the optimal purity levels for a reliable, cost-efficient, aerospace-grade LCH4/LNG fuel. The current work explores various blends of natural gas/methane fuel with various impurities, including higher hydrocarbons as well as nitrogen-carriers. A shock tube study was carried out to study the ignition delay times and carbon monoxide time histories of these natural gas blends utilizing chemiluminescence and laser absorption spectroscopy at 20, 50 and 100 atm over temperatures ranging from 1400-1700K and at an equivalence ratio of 1. The experimental data was then compared to two different chemical kinetic mechanisms: the industry-standard GRI 3.0 and the in-house UCF 2022. The data is used to improve chemical kinetic mechanisms and modeling of LNG fuels for rocket engine applications.

Methane↗

A Bottom-Up Cost Estimation Tool for Nuclear Microreactors

The rising interest in nuclear microreactors has highlighted the need for comprehensive technoeconomic assessments. However, the scarcity of publicly available designs and cost data has posed significant challenges. To address this issue, the Microreactor Optimization Using Simulation and Economics (MOUSE) tool is developed. MOUSE is a tool that integrates nuclear microreactor design with reactor economics. The design calculations encompass core simulations using the OpenMC Monte Carlo Particle Transport Code [romano2015], along with simplified balance of plant calculations. On the economic side, MOUSE provides detailed bottom-up cost estimates, calculating both the total capital cost and the levelized cost of energy for first-of-a-kind and nth-of-a-kind microreactors. The cost estimation correlations are developed using data from the MARVEL project and additional literature sources. MOUSE has released as an open-source tool on GitHub (MOUSE Tool). By combining design calculations with cost equations, MOUSE enables users to evaluate the impact of various technological consideration, advanced moderators, design changes, material/fuel changes, and geometry modifications—as well as economic parameters like interest rates and construction duration. This comprehensive framework can guide stakeholders towards technological solutions that enhance microreactor competitiveness. Additionally, powered by the WATTS toolkit [romano2022], MOUSE supports optimization studies, parametric analyses, and uncertainty calculations/propagation. Currently, preconceptual designs of three microreactor types are included in MOUSE: a liquid metal thermal microreactor (LTMR), gas cooled TRISO-fueled microreactor (GCMR) and heat-pipe TRISO fueled microreactor (HPMR). To showcase its ability, MOUSE was used to conduct detailed bottom-up cost estimates for the first of a kind (FOAK) and Nth of a kind (NOAK) of the following microreactors • A 20MWt LTMR that is built on the ongoing MARVEL demonstration at Idaho National Laboratory (INL) • A 15 MWt GCMR that was designed to be more representative of the typical commercial microreactor • A 7 MWt HPMR that was built on previous work (Choi 2024) The The reader should note that these three designs and corresponding cost estimates are examples to demonstrate the MOUSE capability. The designs are pre-conceptual, the reactor designs were not optimized, and the cost estimates were developed with incomplete information. Additionally, stakeholders might be interested in a variety of designs that may differ from the examples provided in this report. The MOUSE tool can also be used to study how design choices affect economics. To demonstrate its capability, MOUSE was used conduct parametric studies such as examining the economic impact of the reflector's material and thickness, the moderator's booster material and dimensions, fuel composition and enrichment, core size, and power level. Several insights were gained from these parametric studies.

Hanna, Botros↗

Minimized aging of isocyanurate-based rigid cellular foams for buildings through tailored barrier facers and optimized formulation

The thermal resistivity (h·ft 2 ·°F/Btu/in.) of closed-cell rigid foam insulation materials significantly decreases over time. Diffusion-tight facers are designed to significantly enhance initial thermal resistivity and long-term thermal performance by preventing gas diffusion into the foam cells and inhibiting the escape of low thermal conductivity blowing agents. In addition to the gas diffusion property of the facer film, adhesion between the foam and the facer is crucial for achieving diffusion-tight bonding. Here, this study addresses the challenge of thermal aging by investigating how facer film properties and foam formulation influence the durability of thermal performance. A systematic evaluation was conducted to understand the effects of polymeric barrier films, surface treatments, facer coverage, and foam matrix rigidity on thermal resistivity over time. Key findings reveal that diffusion-tight facers, particularly those with metallized layers and compatible heat seal layers, significantly reduce gas exchange and improve foam-facer adhesion. The optimized system, incorporating barrier facers and a tailored polyisocyanurate foam formulation, achieved initial and aged thermal resistivity values after 200 days of approximately 8.3 and 7.4 h ft 2 ·°F/Btu/in., respectively representing only a 10 % reduction compared to a 17 % reduction observed in control samples without facers. Notably, polyurethane spray foams with facers exhibited only a 4 % reduction in thermal resistivity, compared to a 23 % decrease in control samples, demonstrating nearly six times better retention of thermal performance. This innovative facer technology presents a promising solution for reducing energy costs and represents a significant advancement in optimizing energy management for building envelopes in future technologies. This technology can also be adapted for other applications that necessitate the preservation of long-term thermal performance.

Wanasinghe, Shiwanka Vidarshi [Oak Ridge National ↗

Orbit Optimization For The Geospace Electrodynamics Connections (GEC) Mission

Part of NASA's Solar Terrestrial Probe line of missions, the Geospace Electrodynamics Connections (GEC) mission will deploy a formation of three spacecraft to perform in-situ atmospheric research in the low Ionosphere-Thermosphere region. These spacecraft will fly together in a %tring-of-pearls formation with variable spacings ranging from 10 seconds to one-quarter of an orbit at perigee. Over the course of its two-year mission, the three spacecraft will perform ten, 1-week dipping campaigns whereby they maneuver to lower their perigee to near 134 km. Using available launch vehicle performance data, an optimal parking orbit of 222 x 1525 km was found to maximize the dry mass available while providing enough propellant to perform the ten deep-dipping campaigns over its two-year mission. The results were used to create multi-variable contour plots containing the orbit perigee, the orbit apogee, spacecraft dry mass, propellant mass, and T500 (a science data collection figure of merit that tabulates the cumulative time spent below 500 km). These plots illustrate how the mission can trade off science return relative to the cost in dry mass and propellant. Other optimal solutions such as minimum propellant or maximum T500 were found to either limit the science data collection or to be dry mass limiting, respectively. Sensitivity analyses were performed to find new optimal (maximum dry mass) solutions if the number of campaigns changed, if the coefficient of drag (CD) were different, and if the propellant specific impulse were increased. A surprising result showed that the dry mass and T500 were both increased if the number of campaigns decreased. Changes in CD provided the expected results - raising CD lowered both the dry mass and T500 while lowering CD raised both the dry mass and T500. Increases in the propellant specific impulse had the expected outcome of raising the dry mass and lowering the propellant load but there was no change in the T500 figure of merit. The orbit optimization was performed parametrically using a Matlab(TradeMark) script and validated using FreeFlyer(TradeMark), a commercial orbit analysis tool. ,

Mesarch, Michael A.↗

Optimal design of solidification processes

An optimal design algorithm is presented for the analysis of general solidification processes, and is demonstrated for the growth of GaAs crystals in a Bridgman furnace. The system is optimal in the sense that the prespecified temperature distribution in the solidifying materials is obtained to maximize product quality. The optimization uses traditional numerical programming techniques which require the evaluation of cost and constraint functions and their sensitivities. The finite element method is incorporated to analyze the crystal solidification problem, evaluate the cost and constraint functions, and compute the sensitivities. These techniques are demonstrated in the crystal growth application by determining an optimal furnace wall temperature distribution to obtain the desired temperature profile in the crystal, and hence to maximize the crystal's quality. Several numerical optimization algorithms are studied to determine the proper convergence criteria, effective 1-D search strategies, appropriate forms of the cost and constraint functions, etc. In particular, we incorporate the conjugate gradient and quasi-Newton methods for unconstrained problems. The efficiency and effectiveness of each algorithm is presented in the example problem.

Dantzig, Jonathan A.↗

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional–structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional–structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

Role of Cryogenic Aerodynamic Testing for Current and Future Technologies

The motivation for cryogenic wind tunnels originated during the 1960s from an internationally recognized need for a high Reynolds number test capability based on experiences with preflight predictions of aerodynamic characteristics and an anticipated need in support of research and development for future aerospace vehicle systems. More specifically, the motivation for a flight (or near flight) Reynolds number ground test facility was captured in the foreword to reference 1 which states:“...AGARD held a Specialists’ Meeting in Paris on ‘Transonic Aerodynamics’ in recognition of the fact that the absence of adequate theoretical methods and wind tunnels of high enough Reynolds number had already led to costly shortcomings in the transonic performance of certain combat and transport aircraft.” Preflight prediction of flight characteristics is a necessary process for the developer of any aerospace vehicle, and introduces significant risk to the success of the vehicle. Whether the vehicle customer is commercial or governmental, the final full-scale vehicle must meet certain requirements to be certified as safe, and certain performance requirements to be economically successful. Aircraft companies strive to know the flight characteristics and performance of their vehicle with high confidence prior to flight, thus enabling optimal design trades and elimination of any costly modifications to the aircraft during and after initial flight testing. The problems of predicting flight characteristics across the full flight envelope prior to flight have been and continue to be challenging. Much has changed since the US National Transonic Facility (NTF) became operational in the 1980s, followed by the European Transonic Windtunnel (ETW) in 1990s, not the least of which has been the advancement and positive impact of computational fluid dynamics (CFD) on aircraft design and development. Today, the need for integrated CFD and ground-based high Reynolds number test and evaluation capability remains as aerodynamics will always be central to defining an aircraft directly as well as providing critical input to other disciplines. Today the economic stakes of being surprised during flight tests are higher than ever. This oral-only presentation describes the past, current, and future role of high Reynolds number aerodynamic testing in aerospace vehicle design and development. Discussion of relevant flow physics, past experiences with preflight prediction, and future needs, challenges, and opportunities is included. 1.“Facilities and Techniques for Aerodynamic Testing at Transonic Speeds and High Reynolds Number,” AGARD CP-83-71, 1971.

Aerodynamics↗

Optimal Feedback Control of Thermal Networks

An improved approach to the mathematical modeling of feedback control of thermal networks has been devised. Heretofore software for feedback control of thermal networks has been developed by time-consuming trial-and-error methods that depend on engineers expertise. In contrast, the present approach is a systematic means of developing algorithms for feedback control that is optimal in the sense that it combines performance with low cost of implementation. An additional advantage of the present approach is that a thermal engineer need not be expert in control theory. Thermal networks are lumped-parameter approximations used to represent complex thermal systems. Thermal networks are closely related to electrical networks commonly represented by lumped-parameter circuit diagrams. Like such electrical circuits, thermal networks are mathematically modeled by systems of differential-algebraic equations (DAEs) that is, ordinary differential equations subject to a set of algebraic constraints. In the present approach, emphasis is placed on applications in which thermal networks are subject to constant disturbances and, therefore, integral control action is necessary to obtain steady-state responses. The mathematical development of the present approach begins with the derivation of optimal integral-control laws via minimization of an appropriate cost functional that involves augmented state vectors. Subsequently, classical variational arguments provide optimality conditions in the form of the Hamiltonian equations for the standard linear-quadratic-regulator (LQR) problem. These equations are reduced to an algebraic Riccati equation (ARE) with respect to the augmented state vector. The solution of the ARE leads to the direct computation of the optimal proportional- and integral-feedback control gains. In cases of very complex networks, large numbers of state variables make it difficult to implement optimal controllers in the manner described in the preceding paragraph.

Papalexandris, Miltiadis↗

Modeling and Simulation Reliable Spacecraft On-Board Computing

The proposed project will investigate modeling and simulation-driven testing and fault tolerance schemes for Spacecraft On-Board Computing, thereby achieving reliable spacecraft telecommunication. A spacecraft communication system has inherent capabilities of providing multipoint and broadcast transmission, connectivity between any two distant nodes within a wide-area coverage, quick network configuration /reconfiguration, rapid allocation of space segment capacity, and distance-insensitive cost. To realize the capabilities above mentioned, both the size and cost of the ground-station terminals have to be reduced by using reliable, high-throughput, fast and cost-effective on-board computing system which has been known to be a critical contributor to the overall performance of space mission deployment. Controlled vulnerability of mission data (measured in sensitivity), improved performance (measured in throughput and delay) and fault tolerance (measured in reliability) are some of the most important features of these systems. The system should be thoroughly tested and diagnosed before employing a fault tolerance into the system. Testing and fault tolerance strategies should be driven by accurate performance models (i.e. throughput, delay, reliability and sensitivity) to find an optimal solution in terms of reliability and cost. The modeling and simulation tools will be integrated with a system architecture module, a testing module and a module for fault tolerance all of which interacting through a centered graphical user interface.

Park, Nohpill↗

Optimality of incompletely measurable active and passive attitude control systems

Passive attitude control systems and active systems with incomplete state measurements are only suboptimal systems in the sense of optimal control theory, since optimal systems require complete state measurements or state estimations. An optimal system, then, requires additional hardware (especially in the case of flexible spacecraft) which results in higher costs. Therefore, it is a real engineering problem to determine how much an optimal system exceeds the suboptimal system, or in other words, what is the suboptimal system's degree of optimality. The problem will be treated in three steps: (1) definition of the degree of optimality for linear, time-invariant systems; (2) a computation method using the quadratic cost functional; (3) application to a gravity-gradient stabilized three-body satellite and a spinning flexible satellite.

Schiehlen, W.↗