Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Handling”

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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Constructing the Pareto front for multi-objective Markov chains handling a strong Pareto policy approach

In this paper, we present a multi-objective solution of the Pareto front for a certain class of discrete-time ergodic controllable Markov chains. For solving the problem, we transform the original multi-objective problem into an equivalent nonlinear programming problem implementing the Lagrange principle. We then propose to adopt the Tikhonov’s regularization method to ensure the convergence of the cost functions to a unique point into the Pareto front. We show that Pareto policies are characterized as optimal policies. One of the fundamental problems related to the construction of the Pareto front is the existence and characterization of both, Pareto and strong Pareto policies. By introducing the Tikhonov’s regularizator, we ensure the existence of strong Pareto policies. This paper proposes a real solution to this problem. We formulate the original problem considering several constraints: (a) we employ the c-variable method for the introduction of linear constraints over the nonlinear problem and (b) restrict the cost functions, allowing points in the Pareto front to have a small distance from one another. The constraints imposed by the c-variable method make the problem computationally tractable and the restriction imposed by the small distance change ensures the continuation of the Pareto front. The resulting equation in this nonlinear system is an optimization problem for which the necessary and efficient condition of a minimum is solved using the projected gradient method. Moreover, we also prove the convergence conditions and compute the estimate rate of convergence of variables corresponding to the Lagrange principle and the Tikhonov’s regularization, respectively. We provide all the details needed to implement the proposed method in an efficient way. The usefulness of the method is successfully demonstrated by a numerical example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dynamo: Handling Scientific Data Across Sites and Storage Media

Abstract Dynamo is a full-stack software solution for scientific data management. Dynamo’s architecture is modular, extensible, and customizable, making the software suitable for managing data in a wide range of installation scales, from a few terabytes stored at a single location to hundreds of petabytes distributed across a worldwide computing grid. This article documents the core system design of Dynamo and describes the applications that implement various data management tasks. A brief report is also given on the operational experiences of the system at the CMS experiment at the CERN Large Hadron Collider and at a small-scale analysis facility.

Iiyama, Yutaro (ORCID:0000000282975930)↗
DOE OSTI2022

Optimal control to handle variations in moisture content and reactor in-feed rate

The variations in feedstock characteristics, such as moisture and particle size distribution, lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass pre-processing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by up to 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. Additionally, HPC reduces the cost of processing biomass by 0.36%–2.22%, and reduces processing time by 0.35%-2.24%. Furthermore, a biorefinery can adapt HPC to achieve its design capacity.

09 BIOMASS FUELS↗
DOE OSTI2019

A Combined Spin-Flip and IP/EA Approach for Handling Spin and Spatial Degeneracies: Application to Double Exchange Systems

Many multiconfigurational systems, such as single-molecule magnets, are difficult to study using traditional computational methods due to the simultaneous existence of both spin and spatial degeneracies. In this work, a new approach termed n -spin-flip ionization potential/electron affinity ( n SF-IP or n SF-EA) is introduced which combines the spin-flip method of Anna Krylov with particle-number changing IP/EA methods. We demonstrate the efficacy of the approach by applying it to the strongly correlated N 2 + , as well as several double exchange systems. We also demonstrate that when these systems are well-described by a double exchange model Hamiltonian, only 1SF-IP/EA is required to extract the double exchange parameters and accurately predict energies for the low-spin states. This significantly reduces the computational effort for studying such systems. The results of including additional excitations (using a RAS- n SF-IP/EA scheme) are also researched, with particular emphasis on hole and particle excitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Local Chain Dynamics in Sequence-Controlled Polymers as a Tunable Handle for Rare Earth Sequestration

Chain dynamics govern the intricate behaviors of proteins, underpinning functions such as catalysis, recognition, and stimulus response, and are an increasingly appreciated aspect of structure–function relationships. Analogously, manipulating chain dynamics and structure in abiotic polymers via sequence control is an exciting, yet underexplored, strategy for improving material functions. In this work, we report a systematic study relating the sequence of polymeric sequestrants to their structure and dynamics, as well as to their binding affinity and selectivity for model substrates, rare earth elements (REEs). A series of sequence-controlled polymers with metal chelating, solubilizing, and structure forming monomers was synthesized via multiblock polymerization, yielding compositionally identical polymers with spectroscopically resolved domains and distinct morphologies. Using a combination of small-angle X-ray scattering and 19 F NMR relaxometry measurements, we connected differences in polymer structure and dynamics to polymer sequence variables such as the patchiness (density) of the structure forming monomer and the location of the chelating monomer. Furthermore, we found that, relative to calcium, all polymers in the series collapse more and have slower dynamics when binding REEs (lanthanum and lutetium) , though the extent of these effects were sequence-dependent and localized to specific domains within the polymer. Notably, sequence-controlled polymers that exhibited the largest conformational and dynamic changes upon binding REEs also bound REEs with the greatest affinity and modest selectivity. Collectively, these results correlate monomer patterning with dynamics, morphology, and REE binding performance en route to the development of efficient and selective macromolecular chelators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗