Search NASA⌕ Search

SEARCH · Search NASA

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.

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

At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Derivatives of buckling loads and vibration frequencies with respect to stiffness and initial strain parameters

A uniform variational approach to sensitivity analysis of vibration frequencies and bifurcation loads of nonlinear structures is developed. Two methods of calculating the sensitivities of bifurcation buckling loads and vibration frequencies of nonlinear structures, with respect to stiffness and initial strain parameters, are presented. A direct method requires calculation of derivatives of the prebuckling state with respect to these parameters. An adjoint method bypasses the need for these derivatives by using instead the strain field associated with the second-order postbuckling state. An operator notation is used and the derivation is based on the principle of virtual work. The derivative computations are easily implemented in structural analysis programs. This is demonstrated by examples using a general purpose, finite element program and a shell-of-revolution program.

Haftka, Raphael T.↗
NASA NTRS2009

Lunar Exploration Architecture Level Key Drivers and Sensitivities

Strategic level analysis of the integrated behavior of lunar transportation and lunar surface systems architecture options is performed to assess the benefit, viability, affordability, and robustness of system design choices. This analysis employs both deterministic and probabilistic modeling techniques so that the extent of potential future uncertainties associated with each option are properly characterized. The results of these analyses are summarized in a predefined set of high-level Figures of Merit (FOMs) so as to provide senior NASA Constellation Program (CxP) and Exploration Systems Mission Directorate (ESMD) management with pertinent information to better inform strategic level decision making. The strategic level exploration architecture model is designed to perform analysis at as high a level as possible but still capture those details that have major impacts on system performance. The strategic analysis methodology focuses on integrated performance, affordability, and risk analysis, and captures the linkages and feedbacks between these three areas. Each of these results leads into the determination of the high-level FOMs. This strategic level analysis methodology has been previously applied to Space Shuttle and International Space Station assessments and is now being applied to the development of the Constellation Program point-of-departure lunar architecture. This paper provides an overview of the strategic analysis methodology and the lunar exploration architecture analyses to date. In studying these analysis results, the strategic analysis team has identified and characterized key drivers affecting the integrated architecture behavior. These key drivers include inclusion of a cargo lander, mission rate, mission location, fixed-versus- variable costs/return on investment, and the requirement for probabilistic analysis. Results of sensitivity analysis performed on lunar exploration architecture scenarios are also presented.

Goodliff, Kandyce↗
DOE OSTI2019

A Mechanistic Model for Relative Permeability of Gas and Water Flow in Hydrate-Bearing Porous Media With Capillarity

Lack of mechanistic models to describe petrophysical properties of mobile phases in gas hydrate–bearing sediments is one of the key challenges in accurately predicting gas production. The major drawback of empirical models that are used to fit a relative permeability curve for mobile phases in gas hydrate–bearing sediments is that they are based on experimental data, which are limited, and not able to account for hydrate morphology in pore space. This study proposes a relative permeability model that is mechanistic in nature and developed to account capillarity by building on the original nonempirical relative permeability model that assumes negligible capillary pressure. The proposed model implicitly accounts for capillarity with the help of four empirical parameters (two for each mobile phase) that incorporate each mobile phase pressure. It is shown that the proposed model provides an improved match to relative permeability data (derived from pore–scale simulation of gas hydrate–bearing sediments) than nonempirical relative permeability by accounting for the effect of capillary pressure. Additionally, unlike fully empirical models that can predict relative permeabilities reliably only at gas hydrate saturations for which experimental data are available, the proposed model only requires fitting the empirical parameters once with experimental data at any single gas hydrate saturation and then it can then be used to predict relative permeability at any gas hydrate saturation. Here, the mechanistic nature of the proposed model allows studying relative permeability of hydrate–bearing sediments as a function of hydrate morphology and wettability (fluid phase distribution) besides other physical parameters of the model (e.g., porosity, gas, and water residual saturation). Based on the sensitivity analysis of different hydrate morphologies on gas/water relative permeability, it is found that gas relative permeability is sensitive to hydrate morphologies, while water relative permeability shows little dependency on hydrate localization in pore space.

58 GEOSCIENCES↗
DOE OSTI2020

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2003

CFD Variability for a Civil Transport Aircraft Near Buffet-Onset Conditions

A CFD sensitivity analysis is conducted for an aircraft at several conditions, including flow with substantial separation (buffet onset). The sensitivity is studied using two different Navier-Stokes computer codes, three different turbulence models, and two different grid treatments of the wing trailing edge. This effort is a follow-on to an earlier study of CFD variation over a different aircraft in buffet onset conditions. Similar to the earlier study, the turbulence model is found to have the largest effect, with a variation of 3.8% in lift at the buffet onset angle of attack. Drag and moment variation are 2.9% and 23.6%, respectively. The variations due to code and trailing edge cap grid are smaller than that due to turbulence model. Overall, the combined approximate error band in CFD due to code, turbulence model, and trailing edge treatment at the buffet onset angle of attack are: 4% in lift, 3% in drag, and 31% in moment. The CFD results show similar trends to flight test data, but also exhibit a lift curve break not seen in the data.

Rumsey, Christopher L.↗
NASA NTRS2006

NAVIGATION PERFORMANCE IN HIGH EARTH ORBITS USING NAVIGATOR GPS RECEIVER

NASA GSFC has developed a GPS receiver that can acquire and track GPS signals with sensitivity significantly lower than conventional GPS receivers. This opens up the possibility of using GPS based navigation for missions in high altitude orbit, such as Geostationary Operational Environmental Satellites (GOES) in a geostationary orbit, and the Magnetospheric MultiScale (MMS) Mission, in highly eccentric orbits extending to 12 Earth radii and higher. Indeed much research has been performed to study the feasibility of using GPS navigation in high Earth orbits and the performance achievable. Recently, GSFC has conducted a series of hardware in-the-loop tests to assess the performance of this new GPS receiver in various high Earth orbits of interest. Tracking GPS signals to down to approximately 22-25 dB-Hz, including signals from the GPS transmitter side-lobes, steady-state navigation performance in a geostationary orbit is on the order of 10 meters. This paper presents the results of these tests, as well as sensitivity analysis to such factors as ionosphere masks, use of GPS side-lobe signals, and GPS receiver sensitivity.

Bamford, William↗
DOE OSTI2019

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities: Preprint

Increased penetration of distributed variable re-newable generation may cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But due to the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network is needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69 node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

Mid-L/D Lifting Body Entry Demise Analysis

The mid-lift-to-drag ratio (mid-L/D) lifting body is a fully autonomous spacecraft under design at NASA for enabling a rapid return of scientific payloads from the International Space Station (ISS). For contingency planning and risk assessment for the Earth-return trajectory, an entry demise analysis was performed to examine three potential failure scenarios: (1) nominal entry interface conditions with loss of control, (2) controlled entry at maximum flight path angle, and (3) controlled entry at minimum flight path angle. The objectives of the analysis were to predict the spacecraft breakup sequence and timeline, determine debris survival, and calculate the debris dispersion footprint. Sensitivity analysis was also performed to determine the effect of the initial pitch rate on the spacecraft stability and breakup during the entry. This report describes the mid-L/D lifting body and presents the results of the entry demise and sensitivity analyses.

Ling, Lisa↗
DOE OSTI2021

A hybrid data–model approach to map soil thickness in mountain hillslopes

Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

58 GEOSCIENCES↗
DOE OSTI2018

Quantitative Extraction and Mass Spectrometry Analysis at a Single-Cell Level

Quantitative live cell mass spectrometry analysis at a subcellular level requires the precisely controlled extraction of subpicoliter volumes of material from the cell, sensitive analysis of the extracted analytes, and their accurate quantification without prior separation. In this study, we demonstrate that localized electroosmotic extraction provides a direct path to addressing this challenge. Specifically, we demonstrate quantitative mass spectrometry analysis of biomolecules in picoliter volumes extracted from live cells. Electroosmotic extraction was performed using two electrodes and a finely pulled nanopipette with tip diameter of <1 µm containing a hydrophobic electrolyte compatible with mass spectrometry analysis. The electroosmotic drag was used to drive analytes out of the cell into the nanopipette. Analyte molecules extracted both from solutions and cell samples were analyzed using nanoelectrospray ionization (nanoESI) directly from the nanopipette into a mass spectrometer. More than 50 metabolites including sugars and flavonoids were detected in positive mode in 2-5 pL volumes of the cytoplasmic material extracted from Allium cepa. Quantification of the extracted glucose was performed using sequential extraction of a known volume of the aqueous solution containing glucose-d2 standard of known concentration. We found that the ratio of the signal of glucose to glucose-d2 increased linearly with glucose concentration. This observation indicates that the approach developed in this study enables quantitative analysis of small volumes of metabolites extracted from cells. Furthermore, we observed efficient separation of hydrophilic and hydrophobic analytes through partitioning into the aqueous and hydrophobic electrolyte phase, respectively, which provides additional important information on the molecular properties of extracted metabolites.

Yin, Ruichuan↗
DOE OSTI2023

Evaluation of Rail Decarbonization Alternatives: Framework and Application

The Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment requirements, the associated optimal charging/fueling facility location and sizing problem are solved with a five-step framework. Life-cycle analysis (LCA) and techno-economic analysis (TEA) are used to estimate carbon reduction, capital investments, cost of carbon reduction, and operational impacts, enabling sensitivity analysis with operational and technological parameters. Here, the framework is illustrated on lower-carbon drop-in fuels as well as battery-electric technology deployments for the US Eastern and Western Class I railroad networks. Drop-in fuel deployments are modeled as admixtures with diesel in existing locomotives, while battery-electric deployments are shown for varying technology penetration levels and locomotive ranges. When mixed in a 50% ratio with diesel, results show biodiesel’s capacity to reduce emissions at 36% with a cost of $\$$ 0.13 per kilogram of CO 2 reduced, while e-fuels offer a potential reduction of 50% of emissions at a cost of $\$$ 0.22 per kilogram of CO 2 reduced. Battery-electric results for 50% deployment over all ton-miles highlight the value of future innovations in battery energy densities as scenarios assuming 800-mi range locomotives show an estimated emissions reduction of 46% with a cost of $\$$ 0.06 per kilogram of CO 2 reduced, compared with 16% emissions reduction at a cost of $\$$ 0.11 per kilogram of CO 2 reduced for 400-mi range locomotives. The NUFRIEND framework provides a systematic method for comparing different alternative energy technologies and identifying potential challenges and benefits in their future deployments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Effects of Gasoline Composition and Operating Parameters on the Response of End-Gas Autoignition to Nitric Oxide in a Lean-Burn DI-SI Engine

Lean operation of spark-ignition engines can lead to engine thermal efficiency gains and lower NOx emissions due to reduced combustion temperatures. Yet, lean operation could still face challenges in end-gas autoignition and knock generation due to higher intake pressures and trapped NO in the residual gas. Here, this study evaluates the impact of NO on end-gas autoignition for two gasoline fuels with similar octane rating but different composition: high cycloalkane fuel (HCA) and high olefin fuel (HO). Experiments were performed at stoichiometric and lean (λ = 2) conditions and at two engine speeds of 1400 rpm and 2000 rpm. Accompanying chemical kinetics simulations in CHEMKIN revealed that the mechanisms controlling the effect of NO on autoignition are similar λ = 2 and λ = 1, with NO + HO 2 = NO 2 + OH being the main pathway for enhancing reactivity by promoting low-temperature heat release (LTHR). The compositionally different fuels reacted differently to NO seeding and engine speed, and differences were augmented at λ = 2 compared to λ = 1 as the end-gas autoignition shifted to the low temperature regime. HO, which has inherent low temperature chemistry, was strongly impacted by engine speed at low NO seeding levels, with no noticeable peak of LTHR detected at 2000 rpm. On the other hand, LTHR of HCA was marginally affected by shortened residence time at higher engine speed as NO + HO 2 reaction was not greatly affected by shorter time scales, since HO 2 production was sustained even at 2000 rpm to support OH generation from NO + HO 2 . Contrary to HO, HCA exhibited greater sensitivity to NO seeding, as the increased OH production at higher NO concentrations offset the OH-quenching effect of cyclopentane, which accounts for 28.6% of HCA’s composition. Consequently, a sensitivity analysis revealed that fuels with weak inherent low-temperature chemistry, like HCA, are likely to be more sensitive to variations in NO concentration and charge temperature, whereas fuels with strong low temperature chemistry are more sensitive to variations in end-gas λ and intake pressure.

Energy↗
DOE OSTI2026

Implementing belowground controls on nutrient uptake in ELMv2-SPRUCE improves representation of a boreal peatland ecosystem

Boreal peatlands store 13 %–32 % of the global soil carbon (C) stock, a service dependent on plant-mycorrhizal fungi associations. In these nutrient poor systems, ectomycorrhizal and ericoid mycorrhizal fungi supply up to >80 % of the nutrient requirements of their plant hosts, partly with mined nitrogen (N) and phosphorus (P) from soil organic matter that are otherwise inaccessible to plants. Despite the ecological significance, mycorrhizal associations are only represented in a few land surface or ecosystem models. We modify the peatland branch of version 2 of the Energy Exascale Earth System Land Model (ELMv2-SPRUCE) to replace the default photosynthesis-driven inorganic N and P (NP) uptake process with a more realistic representation of the process via three pathways: (1) direct inorganic NP uptake by uncolonized fine roots, (2) indirect inorganic NP acquisition and (3) indirect NP acquisition from organic sources by mycorrhizal roots. We systematically evaluated the performance of the default and modified models with field observations from a whole ecosystem warming and carbon dioxide fertilization experimental site: Spruce and Peatland Responses Under Changing Environment (SPRUCE), in northern Minnesota, USA. The modified model reduces the underestimation of the growth response of shrubs in the default model to warming from 40 %–80 % to 17 %–35 % and reduces the overall relative absolute error on C fluxes from 1.61 to 1.54 in calibration. Improvements on modeled shrub growths and shrub-moss community net ecosystem exchanges are also seen in validation. The improved growth response of shrubs to warming is accompanied by several-fold increase in direct inorganic NP uptake and decrease in fungal colonization rate. The modified model simulates a smaller magnitude of transition of the ecosystem from C sink to C source under warming due to alleviation of plant nutrient limitation. Equifinality analysis shows the newly added parameters in the modified model can be constrained by the observed C fluxes. Sensitivity analysis shows the newly added parameters have stronger statistical interactions than the preexisting parameters in the default model. Overall, the modified model is an improvement over the default ELMv2-SPRUCE and will be a useful tool for understanding boreal peatland change.

Wang, Yaoping [Oak Ridge National Laboratory (ORNL↗
NASA NTRS2012

Design and Application of the Exploration Maintainability Analysis Tool

Conducting human exploration missions beyond Low Earth Orbit (LEO) will present unique challenges in the areas of supportability and maintainability. The durations of proposed missions can be relatively long and re-supply of logistics, including maintenance and repair items, will be limited or non-existent. In addition, mass and volume constraints in the transportation system will limit the total amount of logistics that can be flown along with the crew. These constraints will require that new strategies be developed with regards to how spacecraft systems are designed and maintained. NASA is currently developing Design Reference Missions (DRMs) as an initial step in defining future human missions. These DRMs establish destinations and concepts of operation for future missions, and begin to define technology and capability requirements. Because of the unique supportability challenges, historical supportability data and models are not directly applicable for establishing requirements for beyond LEO missions. However, supportability requirements could have a major impact on the development of the DRMs. The mass, volume, and crew resources required to support the mission could all be first order drivers in the design of missions, elements, and operations. Therefore, there is a need for enhanced analysis capabilities to more accurately establish mass, volume, and time requirements for supporting beyond LEO missions. Additionally, as new technologies and operations are proposed to reduce these requirements, it is necessary to have accurate tools to evaluate the efficacy of those approaches. In order to improve the analysis of supportability requirements for beyond LEO missions, the Space Missions Analysis Branch at the NASA Langley Research Center is developing the Exploration Maintainability Analysis Tool (EMAT). This tool is a probabilistic simulator that evaluates the need for repair and maintenance activities during space missions and the logistics and crew requirements to support those activities. Using a Monte Carlo approach, the tool simulates potential failures in defined systems, based on established component reliabilities, and then evaluates the capability of the crew to repair those failures given a defined store of spares and maintenance items. Statistical analysis of Monte Carlo runs provides probabilistic estimates of overall mission safety and reliability. This paper will describe the operation of the EMAT, including historical data sources used to populate the model, simulation processes, and outputs. Analysis results are provided for a candidate exploration system, including baseline estimates of required sparing mass and volume. Sensitivity analysis regarding the effectiveness of proposed strategies to reduce mass and volume requirements and improve mission reliability is included in these results.

Stromgren, Chel↗
DOE OSTI2021

Separations Consortium: Lignin Rich Stream Fractionation and Purification

In support of the Bioenergy Technologies Office in converting lignin to fuels and chemicals, this project develops scalable separations based on membranes and Electordeionization (EDI) to recover low molecular weight (LMW) compounds from lignin rich streams. The project addresses three technology barriers in developing the bioeconomy; (1) Cost of production (2) Selective separation of organic acid species, and (3) Advanced bioprocess development. Specifically, membrane cascades using Tangential Flow Filtration (TFF) are investigated for the recovery of LMW lignin compounds from lignin rich streams such as Alkaline Pretreatment Liquor (APL), Reductive Catalytic Fractionation (RCF) oil, and Catalytic Oxidation oil. Process concepts, including dynamic filtration, are investigated to meet specific performance targets indicated by the consortium's Industrial Advisory Board for the membrane filtration including maintaining permeance > 1 LMH/bar and an overall cost target of < $1/kg of LMW lignin. EDI is investigated as an integral part of the membrane cascade to recover LMW aromatic acids and as an alternative to nanofiltration. Economic analysis of the processes is presented with a focus on minimizing energy consumption and capital expenditure. Furthermore, a sensitivity analysis is presented to identify key cost drivers and optimize holistic process operating conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Component innovations for lower cost mechanical vapor compression

Despite significant capital and operating costs, mechanical vapor compression (MVC) remains the preferred technology for challenging brine concentration applications. Here, this work seeks to assess the dependence of MVC costs on feedwater salinity and desired water recovery and to quantify the value of improved component performance or reduced component costs for reducing the levelized cost of water (LCOW) of MVC. We built a cost optimization model coupling thermophysical, heat and mass transfer, and technoeconomic models to optimize and identify low cost MVC system designs as a function of feedwater salinity and water recovery. The LCOW ranges over 3.6 to 6.1 $\$$/m 3 for seawater feed salinities of 25–150 g/kg and water recoveries of 40–80 %. We then perform sensitivity analysis on parameter inputs to isolate irreducible costs and determine high value component innovation targets. The LCOW was most sensitive to evaporator material costs and performance, including the overall heat transfer coefficient in the evaporator. Process and material innovations such as polymer-composite evaporator tubes that reduce evaporator costs by 25 % without reducing heat transfer performance by more than 10 % would result in MVC cost reductions of 8 %.

42 ENGINEERING↗
DOE OSTI2019

Technical and economic feasibility of solar flat-plate collector thermal energy systems for small and medium manufacturers

Manufacturing industries require process heating for a wide variety of operations, such as drying, cooking, washing, and sterilizing. Studies of industrial energy consumption have shown that more than 50% of industrial heating demand is in the low (<60 °C), medium (60-150 °C), and medium-high (<250 °C) temperature ranges. A significant fraction of this low temperature thermal energy could be generated by commercially available solar flat-plate collector thermal energy systems, which would reduce the use of fossil fuels, energy cost volatility, and carbon emissions. However, manufacturing industries have not been able to take advantage of solar flat-plate collector systems for two main reasons: First, information is not readily available about when and what flat-plate collector system sizes can be economically applied and, second, manufacturers often do not have appropriate personnel or analysis tools to make decisions about installation of solar flat-plate collector systems. The goal of this research is to provide design decision support to small- and medium-sized manufacturers in conducting feasibility analysis for the application of solar flat-plate collector systems in their operations. The $\bar{φ}, f$-chart method and modified $\bar{φ}, f$-chart design method are used to predict the amount of energy collected by solar flat-plate collectors. A simplified model is proposed to assess the cost of solar flat-plate collector energy systems. To demonstrate the presented feasibility analysis methodology, a decision support software application is developed. What-if scenarios are presented for several geographic locations of varying climates. A sensitivity analysis of savings-to-investment ratio (SIR) was performed by changing selected input parameters by ±30% from the base case. It was found that SIR is sensitive to natural gas price, followed by collector area dependent cost, discount rate, cost of the auxiliary gas heater, and cost of the preheating system.

14 SOLAR ENERGY↗