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Results for “Sensitivity analysis”

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.

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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Perioperative Use of Nonsteroidal Anti-inflammatory Drugs Decreases the Risk of Recurrence of Cancer After Colorectal Resection: A Cohort Study Based on Prospective Data

Background: Perioperative use of nonsteroidal anti-inflammatory drugs (NSAIDs) is known to reduce inflammatory response in relation to surgery. Inflammation may promote recurrence of cancer, thus inhibition by use of NSAIDs could reduce recurrence after surgery. Objective: The aim of this study was to examine the association between perioperative use of NSAIDs and cancer recurrence, as well as disease-free survival (DFS) and mortality after colorectal cancer surgery. Methods: This was a cohort study based on data from a prospective clinical database, electronic medical records, and nationwide registers, and included patients from six major colorectal centers in Denmark. The primary outcome was cancer recurrence, while secondary outcomes included 5-year mortality and DFS. Results: Overall, 2308 patients undergoing colorectal cancer surgery between 1 January 2006 and 31 December 2009 were included. A total of 909 patients received at least 2 days of treatment with NSAIDs, of whom 702 (77.2%) received ibuprofen and 204 (22.4%) received diclofenac. Cox regression analysis adjusting for NSAIDs resulted in decreased recurrence risk (adjusted hazard ratio [HR{sub adjusted}] 0.84, 95% confidence interval [CI] 0.72–0.99; p = 0.042). Competing risk analysis confirmed the finding, with an HR{sub adjusted} of 0.76 (95% CI 0.60–0.97; p = 0.026). There was no significant effect on mortality or DFS. Sensitivity analysis of the effect of ibuprofen reported an HR{sub adjusted} of 0.83 (95% CI 0.70–1.00; p = 0.047). In restricted analyses of localized disease only (Union for International Cancer Control [UICC] I–II) and elective surgery only, no effect was found (localized: HR{sub adjusted} 0.81, 95% CI 0.62–1.06, p = 0.12; elective: HR{sub adjusted} 0.85, 95% CI 0.72–1.01, p = 0.063). Conclusions: Perioperative use of NSAIDs was associated with a reduced risk of cancer recurrence after resection for colorectal cancer. No effect on 5-year mortality or DFS was found.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Implementation of a Practical Teaching Course on Protein Engineering

Protein Engineering is a highly evolved field of engineering aimed at developing proteins for specific industrial, medical, and research applications. Here, we present a practical teaching course to demonstrate fundamental techniques used to express, purify and analyze a recombinant protein produced in Escherichia coli—the enhanced green fluorescent protein (eGFP). The methodologies used for eGFP production were introduced sequentially over six laboratory sessions and included (i) bacterial growth, (ii) sonication (for cell lysis), (iii) affinity chromatography and dialysis (for eGFP purification), (iv) bicinchoninic acid (BCA) and fluorometry assays for total protein and eGFP quantification, respectively, and (v) sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for qualitative analysis. All groups were able to isolate the eGFP from the cell lysate with purity levels up to 72%. Additionally, a mass balance analysis performed by the students showed that eGFP yields up to 46% were achieved at the end of the purification process following the adopted procedures. A sensitivity analysis was performed to pinpoint the most critical steps of the downstream processing.

Gomes, Luciana (ORCID:0000000289921097)↗
NASA NTRS1991

An initial investigation into methods of computing transonic aerodynamic sensitivity coefficients

The three dimensional quasi-analytical sensitivity analysis and the ancillary driver programs are developed needed to carry out the studies and perform comparisons. The code is essentially contained in one unified package which includes the following: (1) a three dimensional transonic wing analysis program (ZEBRA); (2) a quasi-analytical portion which determines the matrix elements in the quasi-analytical equations; (3) a method for computing the sensitivity coefficients from the resulting quasi-analytical equations; (4) a package to determine for comparison purposes sensitivity coefficients via the finite difference approach; and (5) a graphics package.

Carlson, Leland A.↗
NASA NTRS2015

Mars Hybrid Propulsion System Trajectory Analysis: Crew Missions - Part I

NASAs Human spaceflight Architecture team is developing a reusable hybrid transportation architecture in which both chemical and electric propulsion systems are used to send crew and cargo to Mars destinations such as Phobos, Deimos, the surface of Mars, and other orbits around Mars. By combining chemical and electrical propulsion into a single space- ship and applying each where it is more effective, the hybrid architecture enables a series of Mars trajectories that are more fuel-efficient than an all chemical architecture without significant increases in flight times. This paper provides the analysis of the interplanetary segments of the three Evolvable Mars Campaign crew missions to Mars using the hybrid transportation architecture. The trajectory analysis provides departure and arrival dates and propellant needs for the three crew missions that are used by the campaign analysis team for campaign build-up and logistics aggregation analysis. Sensitivity analyses were performed to investigate the impact of mass growth, departure window, and propulsion system performance on the hybrid transportation architecture. The results and system analysis from this paper contribute to analyses of the other human spaceflight architecture team tasks and feed into the definition of the Evolvable Mars Campaign.

Chai, Patrick R.↗
DOE OSTI2018

SafeGuards Analysis

The SafeGuards Analysis (SGA) toolkit is an add-on to existing fuel cycle codes that provides safeguards measurement and evaluation modeling capabilities with associated uncertainty quantification and sensitivity analysis techniques. An important feature of the SGA toolbox is that any other fuel cycle or facility-level code (such as VISION, CYCLUS, et al.) can be easily modified to work with SGA. Thus SGA can incorporate any of the other available fuel cycle codes with minimal modification.

Shugart, Nicolas↗
DOE OSTI2025

Economic and environmental performance of biomass gasification for renewable natural gas production in the context of the U.S. natural gas supply

Bioenergy technologies offer potential for reducing greenhouse gas (GHG) emissions. One such promising technology is biomass gasification, which is the conversion of biomass into renewable natural gas (RNG) for use with a natural gas combined-cycle power generation system. However, the associated economic and emission effects need to be better understood to enable optimal decision-making and avoid missed opportunities for enhancing efficiency and increasing system circularity. This analysis explores opportunities to (1) decarbonize natural-gas-based systems and (2) leverage the extensive US natural gas infrastructure to mobilize biomass resources to achieve environmental and economic benefits. Here, in this analysis, the research team used a spatially explicit biomass logistics model (integrated with relevant biomass availability, technoeconomic analysis, and life cycle assessment information) to simulate economically optimal biomass allocation for RNG production and use for decarbonization in the United States. Results show that the United States has the potential to produce 9203 million GJ of RNG within the expected range of $\$$12–30/GJ. Further analyses tested the overall RNG production system's sensitivity to economic and emissions parameters of nine different processes. The sensitivity analysis results indicate that the median carbon abatement cost of RNG is most sensitive to changes in emissions associated with conversion processes and land use changes. These findings provide a deeper understanding of RNG's economic and emission potential for decision-making and guiding future research.

09 BIOMASS FUELS↗
DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A techno-economic assessment of membrane distillation for treatment of Marcellus shale produced water

Membrane distillation (MD) is a promising desalination technology for treatment of high salinity shale gas produced water. Techno-economic assessment (TEA) is necessary for evaluating the economic feasibility of MD for produced water treatment as compared to other shale gas produced water management strategies. A detailed TEA for a hypothetical 0.5 million gallons per day (MGD) direct contact MD (DCMD) that concentrates produced water from 10% (100,000 mg/L) Total Dissolved Solids (TDS) to 30% salinity is presented in this study. The model is developed based on a combination of experimental results, ASPEN Plus process model, best available engineering knowledge, and cost estimates. Analysis reveals that thermal energy cost for MD operation contributes the most to total cost of treating produced water in an MD plant. Additionally, the results of sensitivity analysis reveal that feed TDS level and thermal energy price have a significant impact on total cost of treating produced water. We also explore the implications of utilizing waste heat on the economics of the MD technology for produced water treatment. Here the results reveal that the total cost of treating produced water using MD is $\$$5.70/m 3 feed which decreases significantly to $\$$0.74/m 3 feed when MD is integrated with a source of waste heat.

42 ENGINEERING↗
DOE OSTI2025

Impact of inland boundary conditions on seawater intrusion modeling in stratified coastal aquifers under sea-level rise

This study systematically examines the impact of inland boundary conditions on seawater intrusion modeling in general stratified coastal aquifers under sea-level rise (SLR). We derived analytical solutions for seawater wedge toe positions in stratified aquifers with general head boundary (GHB) conditions and compiled solutions for constant head boundary (CHB), constant flux boundary (CFB), and GHB conditions in both homogeneous and stratified aquifers. Additionally, we introduced the concept of equivalent boundary conditions and developed equations to ensure consistent steady-state toe positions across different boundary types. Unlike previous studies focusing on specific layering configurations, we conducted a comprehensive sensitivity analysis of seawater intrusion in general stratified aquifers using transmissivity centroid elevation (TCE). Our results show that SLR generally exacerbates seawater intrusion, with unconfined aquifers exhibiting higher sensitivity across all boundary conditions. Among boundary types, CHB conditions were the most sensitive to SLR, CFB the least, and GHB showed an intermediate response depending on its distance from the model boundary. Furthermore, seawater intrusion increases with the TCE of the stratified aquifer under SLR, suggesting that high-permeability or preferential flow layers near the surface amplify the impact of SLR. These findings emphasize the importance of selecting appropriate boundary conditions when evaluating SLR-driven seawater intrusion in stratified coastal aquifers.

Boundary condition↗
DOE OSTI2018

Decision Trees for Analysis of Strategies to Deter Limited Nuclear Use in a Generic Scenario

We assert that analysis of a decision tree model can reveal key insights for deterring limited nuclear use in a conventional conflict. To illustrate the method, we develop a decision analysis model to explore the choices an attacker would make and how they can be influenced by his perceptions of the defender’s capabilities and potential responses. Sensitivity analysis with the model can provide insights into strategies and actions the defender might take in order to influence the choices the attacker would make. This methodology is widely applicable and could provide insight into a variety of scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2014

N2A: a computational tool for modeling from neurons to algorithms

The exponential increase in available neural data has combined with the exponential growth in computing (“Moore’s law”) to create new opportunities to understand neural systems at large scale and high detail. The ability to produce large and sophisticated simulations has introduced unique challenges to neuroscientists. Computational models in neuroscience are increasingly broad efforts, often involving the collaboration of experts in different domains. Furthermore, the size and detail of models have grown to levels for which understanding the implications of variability and assumptions is no longer trivial. Here, we introduce the model design platform N2A which aims to facilitate the design and validation of biologically realistic models. N2A uses a hierarchical representation of neural information to enable the integration of models from different users. N2A streamlines computational validation of a model by natively implementing standard tools in sensitivity analysis and uncertainty quantification. The part-relationship representation allows both network-level analysis and dynamical simulations. We will demonstrate how N2A can be used in a range of examples, including a simple Hodgkin-Huxley cable model, basic parameter sensitivity of an 80/20 network, and the expression of the structural plasticity of a growing dendrite and stem cell proliferation and differentiation.

biologically realistic modeling↗
DOE OSTI2025

Uncertainty-Based Design: Finite Element and Explainable Machine Learning Modeling of Carbon–Carbon Composites for Ultra-High Temperature Solar Receivers

Design under uncertainty has significantly grown in research developments during the past decade. Additionally, machine learning (ML) and explainable ML (XML) have offered various opportunities to provide reliable predictable models. The current article investigates the use of finite element modeling (FEM), ML and XML predictions, and uncertain-based design of carbon-carbon (C-C) composites for use in ultra-high temperatures. A C-C composite concentrating solar power (CSP) as a microvascular receiver is considered as a case study. These C-C composites are fiber composites with directly integrated carbonized microchannels to form a lightweight, high-absorptivity material that includes an embedded microvascular network of channels. The topology of these microchannels is engineered to optimize heat transfer to a supercritical carbon dioxide (sCO2) heat transfer fluid. The mechanical characterization of C-C composites is highly challenging. Thus, designing every component made of C-C composites for ultra-high temperature applications needs an uncertainty-based analysis. As a part of a comprehensive project on the development of a novel carbonized microvascular C-C composite, this paper explores C-C composite sensitivity analysis, FEM, ML prediction, and XML analysis. The resulting composite can then be carbonized and coated with an oxidation-resistant coating to form a thermally efficient and mechanically robust C-C composite. An ANSYS 3-D-FE model was used to analyze the CSP’s stress/strain. To consider the variability in the mechanical and thermal properties of C-C composites, various mechanical properties are considered as the ANSYS FEM’s input. A synthetic dataset from 730 ANSYS runs was produced to feed into the ML and XML algorithms for uncertainty analysis and prediction. The ML and XML algorithms could accurately predict the CSP stresses/strains.

Daghigh, Vahid (ORCID:0000000298941620)↗
NASA NTRS1983

Analysis of structural perturbations in systems via cost decomposition methods

It has long been common practice to analyze linear dynamic systems by decomposing the total response in terms of individual contributions which are easier to analyze. Examples of this philosophy include the expansion of transfer functions using: (1) the superposition principle, (2) residue theory and partial fraction expansions, (3) Markov parameters, Hankel matrices, and (4) regular and singular perturbations. This paper summarizes a new and different kind of expansion designed to decompose the norm of the response vector rather than the response vector itself. This is referred to as "cost-decomposition' of the system. The notable advantages of this type of decomposition are: (a) easy application to multi-input, multi-output systems, (b) natural compatibility with Linear Quadratic Gaussian Theory, (c) applicability to the analysis of more general types of structural perturbations involving inputs, outputs, states, parameters. Property (c) makes the method suitable for problems in model reduction, measurement/actuator selections, and sensitivity analysis.

Skelton, R. E.↗
DOE OSTI2017

Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis

In this study, three scenarios are considered to quantify the impact of the biorefinery size on the required biomass logistical resources. The biorefinery scenarios include small scale (175 dt/day)-SS, medium scale (520 dt/day)-MS and large scale (860 dt/day)-LS. These scenarios are compared against the following logistical resources (1) harvest area and contracted fields, (2) logistics equipment fleet and the workforce to run this fleet and (3) intermediate storage sites and their biomass inventory levels. To this end, the IBSAL-MC simulation model is applied to a corn stover logistics system in Southwestern Ontario. The obtained results show (1) the harvest area and the number of contracted fields increase by 65% and 78% from the SS scenario to the MS and LS scenarios, respectively, (2) the average biomass delivered costs are estimated to be $82.09, $87.49 and $93.75/dry tonne in the SS, MS and LS scenarios. The increase in the capital costs to develop a dedicated logistics equipment fleet are estimated to be far greater than the increase in the delivered costs as the size of the biorefinery increases. The upfront capital costs are estimated to be 6.72 dollars, 21.83 and 35.51 million in these scenarios. To run the logistics equipment fleet efficiently, 37, 136 and 235 well-trained operators are required in the SS, MS ad LS scenarios, respectively, and (3) the inventory level and the land requirement for storage in the MS and LS scenarios are estimated to be 225% and 425% greater than those of the SS scenario. The sensitivity analysis indicates that the logistical resources are highly sensitive to corn yield and farm participation rate. Overall, this study shows the importance of considering the size of the required logistical resources and the associated level of logistical complexity in evaluating the economic viability of a biorefinery project.

09 BIOMASS FUELS↗
NASA NTRS2002

Reliability and Productivity Modeling for the Optimization of Separated Spacecraft Interferometers

As technological systems grow in capability, they also grow in complexity. Due to this complexity, it is no longer possible for a designer to use engineering judgement to identify the components that have the largest impact on system life cycle metrics, such as reliability, productivity, cost, and cost effectiveness. One way of identifying these key components is to build quantitative models and analysis tools that can be used to aid the designer in making high level architecture decisions. Once these key components have been identified, two main approaches to improving a system using these components exist: add redundancy or improve the reliability of the component. In reality, the most effective approach to almost any system will be some combination of these two approaches, in varying orders of magnitude for each component. Therefore, this research tries to answer the question of how to divide funds, between adding redundancy and improving the reliability of components, to most cost effectively improve the life cycle metrics of a system. While this question is relevant to any complex system, this research focuses on one type of system in particular: Separate Spacecraft Interferometers (SSI). Quantitative models are developed to analyze the key life cycle metrics of different SSI system architectures. Next, tools are developed to compare a given set of architectures in terms of total performance, by coupling different life cycle metrics together into one performance metric. Optimization tools, such as simulated annealing and genetic algorithms, are then used to search the entire design space to find the "optimal" architecture design. Sensitivity analysis tools have been developed to determine how sensitive the results of these analyses are to uncertain user defined parameters. Finally, several possibilities for the future work that could be done in this area of research are presented.

Kenny, Sean↗
DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗
DOE OSTI2018

ATDM report to ECP AD FY18Q4

A comprehensive V&V study of hypersonic flow in SPARC validated against several experiments was produced. This work was successfully completed as an official ASC L2 milestone with an external review of the team's work. Our work has provided a basis for utilizing SPARC as credible analysis tool for hypersonic re-entry flows. The V&V process has been exercised in full breadth including applicable frameworks, professional standards, code and solution verification, calibration, sensitivity analysis and parametric uncertainty.

97 MATHEMATICS AND COMPUTING↗