SEARCH · Engineering Papers

Results for “Cost allocation”

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.

SourceResearch connectionFrom yearThrough year

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

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

NASA NTRS1971

Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 1: Technical description

The optimal allocation of resources to the national space program over an extended time period requires the solution of a large combinatorial problem in which the program elements are interdependent. The computer model uses an accelerated search technique to solve this problem. The model contains a large number of options selectable by the user to provide flexible input and a broad range of output for use in sensitivity analyses of all entering elements. Examples of these options are budget smoothing under varied appropriation levels, entry of inflation and discount effects, and probabilistic output which provides quantified degrees of certainty that program costs will remain within planned budget. Criteria and related analytic procedures were established for identifying potential new space program directions. Used in combination with the optimal resource allocation model, new space applications can be analyzed in realistic perspective, including the advantage gain from existing space program plant and on-going programs such as the space transportation system.

Source record↗

NASA NTRS2016

Development and Characterization of a Small Spacecraft Electro-Optic Scanner for Free-Space Laser Communications

Emergent data-intensive missions coupled with dramatic reductions in spacecraft size plus an increasing number of space-based missions necessitates new high performance, compact and low cost communications technology. Free space optical communications offer advantages including orders of magnitude increase for data rate performance, increased security, immunity to jamming and lack of frequency allocation requirements when compared with conventional radio frequency (RF) means. The spatial coherence and low divergence associated with the optical frequencies of laser communications lends themselves to superior performance, but this increased directionality also creates one of the primary technical challenges in establishing a laser communications link by repeatedly and reliably pointing the beam onto the receive aperture. Several solutions have emerged from wide angle (slow) mechanical articulation systems, fine (fast) steering mirrors and rotating prisms, inertial compensation gyros and vibration isolation cancellation systems, but each requires moving components and imparts a measured amount of burden on the host platform. The complexity, cost and size of current mechanically scanned solutions limits their platform applicability, and restricts the feasibility of deploying optical communications payloads on very compact spacecraft employing critical systems. A high speed, wide angle, non-mechanical solution is therefore desirable. The purpose of this work is to share the development, testing, and demonstration of a breadboard prototype electro-optic (EO) scanned laser-communication link (see Figure 1). This demonstration is a step toward realizing ultra-low Size, Weight and Power (SWaP) SmallSat/MicroSat EO non-mechanical laser beam steering modules for high bandwidth ( greater than Gbps) free-space data links operating in the 1550 nm wavelength bands. The elimination of all moving parts will dramatically reduce SWaP and cost, increase component lifetime and reliability, and simplify the system design of laser communication modules. This paper describes the target mission architectures and requirements (few cubic centimeters of volume, 10's of grams of weight with milliwatts of power) and design of the beam steering module. Laboratory metrology is used to determine the component performance including horizontal and vertical resolution (20urad) as a function of control voltage (see Figure 2), transition time (0.1-1ms), pointing repeatability and optic insertion loss. A test bed system demonstration, including a full laser communications link, is conducted. The capabilities of this new EO beam steerer provide an opportunity to dramatically improve space communications through increased utilization of laser technology on smaller platforms than were previously attainable.

Laser Optical Communications↗

DOE OSTI2021

A systematic solution to quantify economic values of vehicle grid integration

We report Vehicle-Grid-Integration (VGI) supplies one of the potential benefit extensions for electric vehicles (EVs) to make use of their parking time, which enables the EVs to provide grid services while still meeting consumer driving needs. However, the costs, benefits and risks of VGI still remain unclear, which limits the development of the VGI to promote the interaction between the EV and grid. In this study, we propose an integrated framework to quantify and utilize the aggregate flexibility of the EVs to supply the grid services in electricity markets. The integrated solution includes five sub-modules that cover end-to-end functionalities from individual EV energy consumption estimation to final monetary values calculation of providing grid services. Both wholesale market and local level charging management are formulated in the optimization module. A predictive control algorithm is proposed to allocate power to individual vehicles in real time, considering uncertainties from dispatch signal and travel behavior. Simulation results from 10,000 EVs indicate that the proposed optimization methods can significantly reduce the system cost in both wholesale market and retail market. Local tariff optimization reduces the electricity cost by 24.4% compared to uncontrolled charging. Wholesale market optimization results show that $\$$691 and $\$$255 revenues can be captured by each EV in ERCOT and CAISO markets per year, although with a conservative assumption on battery throughput cost at 0.16$\$$/kWh.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Levelized cost and carbon intensity of solar hydrogen production via water splitting using a scalable and intrinsically safe photocatalytic Z-scheme raceway system

Generating hydrogen from local energy resources such as solar or wind would unlock a low-carbon energy carrier that could be used to reduce greenhouse gas emissions in sectors such as industry and transportation. Yet, the allocation of new or existing power generation solely to hydrogen production remains contentious due to disputes regarding emissions accounting. Photocatalytic (PC) hydrogen production technologies offer a unique solution, as hydrogen is produced directly from solar energy and water, without the need for electricity generation. However, cost projections for all photocatalytic designs to date have suggested that they are not cost competitive compared to conventional electrolysis systems manufactured at scale. Herein, we offer the first illustrative benchmark of cost and carbon intensity of hydrogen produced in a type 2 “Z-scheme” photocatalytic reactor design, which employs suspended semiconducting nanoconductor particles organized into two stacked volumes in a raceway design. The “Z-scheme” system utilizes two separate photoabsorber particles, tuned to drive either the hydrogen evolution reaction or the oxygen evolution reaction individually, connected via a reversible, charge transfer redox couple in solution. Furthermore, the results suggest a highly competitive and scalable technology, that justifies further experimental validation and prototyping in the field.

Carbon↗

DOE OSTI2021

Demonstrating UPC++/Kokkos Interoperability in a Heat Conduction Simulation (Extended Abstract)

We describe the replacement of MPI with UPC++ in an existing Kokkos code that simulates heat conduction within a rectangular 3D object, as well as an analysis of the new code’s performance on CUDA accelerators. The key challenges were packing the halos in Kokkos data structures in a way that allowed for UPC++ remote memory access, and streamlining synchronization costs. Additional UPC++ abstractions used included global pointers, distributed objects, remote procedure calls, and futures. We also make use of the device allocator concept to facilitate data management in memory with unique properties, such as GPUs. Our results demonstrate that despite the algorithm’s good semantic match to message passing abstractions, straightforward modifications to use UPC++ communication deliver vastly improved performance and scalability in the common case. We find the one-sided UPC++ version written in a natural way exhibits good performance, whereas the message-passing version written in a straightforward way exhibits performance anomalies. We argue this represents a productivity benefit for one-sided communication models.

Waters, Daniel↗

NASA NTRS1993

Control structural interaction testbed: A model for multiple flexible body verification

Conventional end-to-end ground tests for verification of control system performance become increasingly complicated with the development of large, multiple flexible body spacecraft structures. The expense of accurately reproducing the on-orbit dynamic environment and the attendant difficulties in reducing and accounting for ground test effects limits the value of these tests. TRW has developed a building block approach whereby a combination of analysis, simulation, and test has replaced end-to-end performance verification by ground test. Tests are performed at the component, subsystem, and system level on engineering testbeds. These tests are aimed at authenticating models to be used in end-to-end performance verification simulations: component and subassembly engineering tests and analyses establish models and critical parameters, unit level engineering and acceptance tests refine models, and subsystem level tests confirm the models' overall behavior. The Precision Control of Agile Spacecraft (PCAS) project has developed a control structural interaction testbed with a multibody flexible structure to investigate new methods of precision control. This testbed is a model for TRW's approach to verifying control system performance. This approach has several advantages: (1) no allocation for test measurement errors is required, increasing flight hardware design allocations; (2) the approach permits greater latitude in investigating off-nominal conditions and parametric sensitivities; and (3) the simulation approach is cost effective, because the investment is in understanding the root behavior of the flight hardware and not in the ground test equipment and environment.

Chory, M. A.↗

DOE OSTI2023

Transactive Emergency Power Allocation

The devastating impacts of extreme weather events, many of which are climate-change related, are increasingly evident through the frequency and duration of outages on power grids, especially the distribution systems. One of the major modern-day concerns of utilities is dealing with such extreme supply outages where operators have used rolling blackouts as a contingency plan balance supply and demand while serving critical loads. Such events have significant repercussions social and economic costs. Such blackouts practices are a blunt instrument, depriving customers with low-capacity high-priority loads (i.e. refrigeration, water, telecommunication, etc.) that provide high marginal amenity. Our contribution presented in this work is a transactive emergency allocation mechanism that would provide some minimum level of service to all of the customers while enabling preference-based trading of this initial allocation. This is in contrast to the state-of-art TE mechanisms that allocate resources to customers solely based on their willingness-to-pay. The effectiveness of the proposed mechanism is demonstrated through simulation-based evaluation on a prototypical distribution system experiencing 12-hour scarcity-based emergency event due to extreme operating conditions. Simulation results clearly demonstrate the capability of the proposed transactive emergency allocation mechanism in effectively utilizing the available energy and providing some level of service to all customers to operate their high-priority loads throughout the extreme scarcity event while being economically efficient in allowing trading of allocation based on customer preferences.

transactive energy, power system economics, emerge↗

DOE OSTI2024

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Aluminum Ultra-conductors for Energy-Efficient Aerospace Busbar Applications (Abstract)

In this project, we will develop aluminum ultra-conductors with graphene additives demonstrating enhanced electrical conductivity at 90 °C compared to electric grade aluminum alloy AA1100 (43% IACS at 90 °C). While ultra-conductivity has been developed in copper and copper alloys, it is yet to be reported extensively in aluminum-based materials. This project will scale initial work done at PNNL on aluminum ultra-conductors using shear-assisted processing and extrusion (ShAPETM), a novel solid phase processing technique. Ultra-conductors are an emerging class of composites, comprised of a metal substrate with small quantities of nanocrystalline additives such as graphene or carbon nanotubes that demonstrate enhanced conductivity at relevant operating temperatures. Aluminum ultra-conductors can improve efficiency and power density while reducing the demand for copper in a wide range of applications, such as power transmission cables and electric motors. Busbars are an important component in aerospace systems that require lightweight and high-current power distribution including both future electric vertical take-off and landing (eVTOL) aircrafts and current aircraft electrical systems. We will accelerate aluminum ultra-conductor composite formulation development using combinatorial synthesis and testing methods aided by process/microstructure modeling, developed previously at PNNL. Eaton will test the properties of the ShAPE aluminum ultra-conductor feedstock (used to make the busbars) in relevant operating conditions (20 – 90 °C), predict the improvement in busbar performance when manufactured with ultra-conductors over commercial conductors (such as AA1100), and perform technoeconomic analysis to evaluate the potential for commercialization of ShAPE aluminum ultra-conductors. The project is expected to have a budget of $\$375$K, with $\$300$K in federal funding and $\$75$K in-kind cost-share contribution from Eaton over a period of performance of 24 months. Of the $\$300$K of federal funds, $\$140$K is allocated for CRADA activities that generate intellectual property (IP), and the remaining $\$160$K is reserved for modeling, material testing, characterization, travel, and reporting-related activities.

36 MATERIALS SCIENCE↗

NASA NTRS1975

Data management for Large Space Telescope

The data management system for the Large Space Telescope (LST) must be capable of meeting requirements of 160 million bits per 95 min orbit with a bit error rate of less than 0.00001 for data. The system will be supported by the Tracking and Data Relay Satellite System of the Space Tracking and Data Network. The on-board system includes a general purpose computer that controls the vehicle as a stable observation platform and the array of instruments used for data collection. The ground-based system comprises a Mission Operations Center (MOC), a Science Institute where instrument data is processed, and a communications service for the space and point-to-point data flow. The allocation of hardware and software between on-board and ground-based components to achieve design objectives of maximum flexibility at minimum cost is discussed.

Hope, G. R., Jr.↗

DOE OSTI2022

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗

DOE OSTI2022

Calibrating the Classical Hardness of the Quantum Approximate Optimization Algorithm

The trading of fidelity for scale enables approximate classical simulators such as matrix product states (MPSs) to run quantum circuits beyond exact methods. A control parameter, the so-called bond dimension $\mathcal{χ}$ for MPSs, governs the allocated computational resources and the output fidelity. Here, we characterize the fidelity for the quantum approximate optimization algorithm by the expectation value of the cost function that it seeks to minimize and find that it follows a scaling law $\mathscr{F}$(ln $\mathcal{χ}$/N), where N is the number of qubits. With ln $\mathcal{χ}$ amounting to the entanglement that a MPS can encode, we show that the relevant variable for investigating the fidelity is the entanglement per qubit. Importantly, our results calibrate the classical computational power required to achieve the desired fidelity and benchmark the performance of quantum hardware in a realistic setup. For instance, we quantify the hardness of performing better classically than a noisy superconducting quantum processor by readily matching its output to the scaling function. Moreover, we relate the global fidelity to that of individual operations and establish its relationship with $\mathcal{χ}$ and N. We sharpen the requirements for noisy quantum computers to outperform classical techniques at running a quantum optimization algorithm in speed, size, and fidelity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1991

Constraint-based scheduling

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Zweben, Monte↗

NASA NTRS1991

Constraint-based scheduling

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocations for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its applications to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Zweben, Monte↗

NASA NTRS1993

Constraint-based scheduling

Zweben, Monte↗

DOE OSTI2021

Coordinated resource allocation to plant growth–defense tradeoffs

Summary Plant resource allocation patterns often reveal tradeoffs that favor growth (G) over defense (D), or vice versa. Ecologists most often explain G–D tradeoffs through principles of economic optimality, in which negative trait correlations are attributed to the reconciliation of fitness costs. Recently, researchers in molecular biology have developed ‘big data’ resources including multi‐omic (e.g. transcriptomic, proteomic and metabolomic) studies that describe the cellular processes controlling gene expression in model species. In this synthesis, we bridge ecological theory with discoveries in multi‐omics biology to better understand how selection has shaped the mechanisms of G–D tradeoffs. Multi‐omic studies reveal strategically coordinated patterns in resource allocation that are enabled by phytohormone crosstalk and transcriptional signal cascades. Coordinated resource allocation justifies the framework of optimality theory, while providing mechanistic insight into the feedbacks and control hubs that calibrate G–D tradeoff commitments. We use the existing literature to describe the coordinated resource allocation hypothesis (CoRAH) that accounts for balanced cellular controls during the expression of G–D tradeoffs, while sustaining stored resource pools to buffer the impacts of future stresses. The integrative mechanisms of the CoRAH unify the supply‐ and demand‐side perspectives of previous G–D tradeoff theories.

Monson, Russell K.↗

NASA NTRS1992

Decision rules for spaceborne operations planning

Recent study of Space Station Freedom requirements for extravehicular activity (EVA) to perform external maintenance tasks emphasize an oversubscription of resources for performing on-orbit tasks. Extravehicular robotics (EVR) and cooperative EVA combined with EVR (using crew and robots synergistically to perform tasks) have been suggested as a part of the solution to reduce EVA. The question remains however, 'Under what conditions is it cost-effective to use the EVA and/or EVR resource.' The answer to such a question also has implications for the Space Station Freedom and its external maintenance as well as the Space Exploration Initiative (SEI) where the issue of work-system allocation is magnified by the long distances and scope of EVA work. This paper describes a simple technique of interest to operational planners and robot technology planners for determining in an economic context whether to use EVA alone, EVR alone, or Cooperative EVA. It is also shown that given: (1) the task times for these alternatives; and (2) the marginal costs of EVA, EVR, and IVA, the appropriate work system for performing the task can be identified. The paper illustrates how the work system choice is based on the ratio of costs. An example using Space Station Freedom data is presented to illustrate the trade-offs among alternative work-systems.

Smith, Jeffrey H.↗