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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Catalytic co-pyrolysis of LDPE and PET with HZSM-5, H-beta, and HY: experiments and kinetic modelling

In this study, the catalytic pyrolysis of low-density polyethylene (LDPE), polyethylene terephthalate (PET) and their mixture (1 : 1 wt/wt) with three zeolite catalysts (HZSM-5, H-beta, HY) was investigated using a thermogravimetric analyzer (TGA) and a Pyroprobe® micro-reactor coupled to a gas chromatograph mass spectrometer (Py-GC/MS). The TGA results demonstrated that during pyrolysis at 10 °C min –1 , on average, zeolite catalysts decreased the maximum decomposition temperature by 149 °C for LDPE while only decreasing by 8 °C for PET. The derivative thermogravimetric (DTG) curve evidenced interactions when the two polymers were catalytically co-pyrolyzed for all the three catalysts. A lumped nth order reaction scheme was able to accurately model both non-catalytic and catalytic pyrolysis and co-pyrolysis by using the least squares fitting approach for determining the kinetic parameters. The kinetic model was able to model well the interaction effects observed during catalytic co-pyrolysis of LDPE and PET with HZSM-5, H-beta, and HY (Fit% Wt% > 96%, Fit% DTG > 94%). Py-GC/MS experiments for the catalytic fast pyrolysis of LDPE revealed that HZSM-5 resulted in the highest selectivity to aromatic hydrocarbons (31.6%) and HY resulted in the highest selectivity to gasoline range C 5 –C 10 paraffins and olefins (40.9%). Catalytic fast pyrolysis of PET showed high selectivity to benzene for all the catalysts (>43%) and that HZSM-5 resulted in the highest selectivity to polyaromatic hydrocarbons (24.7%). Finally, the catalytic fast co-pyrolysis of LDPE and PET revealed interaction effects for all the three catalysts evidenced by a positive synergy% for alkylated benzenes (3–142%) and polyaromatics (105–187%) with a concomitant negative synergy% for benzene (24–36%) and C 5 –C 10 paraffins and olefins (27–53%).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Transient Numerical Modeling of Catalytic Channels

This paper presents a transient model of catalytic combustion suitable for isolated channels and monolith reactors. The model is a lumped two-phase (gas and solid) model where the gas phase is quasi-steady relative to the transient solid. Axial diffusion is neglected in the gas phase; lateral diffusion, however, is accounted for using transfer coefficients. The solid phase includes axial heat conduction and external heat loss due to convection and radiation. The combustion process utilizes detailed gas and surface reaction models. The gas-phase model becomes a system of stiff ordinary differential equations while the solid phase reduces, after discretization, into a system of stiff ordinary differential-algebraic equations. The time evolution of the system came from alternating integrations of the quasi-steady gas and transient solid. This work outlines the numerical model and presents some sensitivity studies on important parameters including internal transfer coefficients, catalytic surface site density, and external heat-loss (if applicable). The model is compared to two experiments using CO fuel: (1) steady-state conversion through an isothermal platinum (Pt) tube and (2) transient propagation of a catalytic reaction inside a small Pt tube. The model requires internal mass-transfer resistance to match the experiments at lower residence times. Under mass-transport limited conditions, the model reasonably predicted exit conversion using global mass-transfer coefficients. Near light-off, the model results did not match the experiment precisely even after adjustment of mass-transfer coefficients. Agreement improved for the first case after adjusting the surface kinetics such that the net rate of CO adsorption increased compared to O2. The CO / O2 surface mechanism came from a sub-set of reactions in a popular CH4 / O2 mechanism. For the second case, predictions improved for lean conditions with increased external heat loss or adjustment of the kinetics as in the first case. Finally, the results show that different initial surface-species distribution leads to different steady-states under certain conditions. These results demonstrate the utility of a lumped two-phase model of a transient catalytic combustor with detailed chemistry.

Struk, Peter M.↗
NASA NTRS2025

Sealing Europa’s Vents By Vapor Deposition: An Order-of-Magnitude Study

Fractures and vents in the ice crust of Europa, exposing the sub-surface ocean or liquid-water inclusions to the vacuum, might be responsible for the generation of planetary-scale water-vapor plumes. During its passage through the ice, the plume vapor is expected to partially condense on the cold ice walls. Together with other effects (water spillage, compression forces, etc.) this mechanism likely contributes to sealing the vent. In this work, we develop a lumped-parameter model to analyze the sealing timescales associated to water-vapor deposition alone. Neglecting all other possible mechanisms, we find shutting-off times roughly compatible with the 7-hour plume observed in 2012 by the Hubble Space Telescope, suggesting that vapor deposition might have played a major role in sealing the vent. A map of sealing times vs. plume density, mass flow rate and aperture areas is given. Plume quantities from the literature are analyzed and compared to our results. For a given plume density/mass flow rate, small apertures would be sealed quickly by vapor deposition and are thus incompatible with observations.

Europa↗
NASA NTRS1978

Creation of lumped parameter thermal model by the use of finite elements

In the finite difference technique, the thermal network is represented by an analogous electrical network. The development of this network model, which is used to describe a physical system, often requires tedious and mental data preparation and checkout by the analyst which can be greatly reduced through the use of the computer programs to develop automatically the mathematical model and associated input data and graphically display the analytical model to facilitate model verification. Three separate programs are involved which are linked through common mass storage files and data card formats. These programs are SPAR, CINGEN and GEOMPLT, and are used to (1) develop thermal models for the MITAS II thermal analyzer program; (2) produce geometry plots of the thermal network; and (3) produce temperature distribution and time history plots.

Source record↗
NASA NTRS2008

Numerical Investigation of LO2 and LCH4 Storage Tanks on the Lunar Surface

Currently NASA is developing technologies to enable human exploration of the lunar surface for duration of up to 210 days. While trade studies are still underway, a cryogenic ascent stage using liquid oxygen (LO2) and liquid methane (LCH4) is being considered for the Altair lunar lander. For a representative Altair cryogenic ascent stage, we present a detailed storage analysis of the LO2 and LCH4 propellant tanks on the lunar surface for durations of up to 210 days. Both the LO2 and LCH4 propellant tanks are assumed to be pressurized with gaseous helium at launch. A two-phase lumped-vapor computational fluid dynamics model has been developed to account for the presence of a noncondensable gas in the ullage. The CFD model is used to simulate the initial pressure response of the propellant tanks while they are subjected to representative heat leak rates on the lunar surface. Once a near stationary state is achieved within the liquid phase, multizone model is used to extrapolate the solution farther in time. For fixed propellant mass and tank size, the long-term pressure response for different helium mass fractions in both the LO2 and LCH4 tanks is examined.

Moder, Jeff↗
NASA NTRS1972

A non-linear dynamic lumped-parameter model of a rectangular plate.

A lumped-parameter model of a rectangular plate is developed by assuming fundamental mode solutions and using Hamilton's Principle and the Euler equations to set up the differential equation of motion for the system. The plate theory used may be described as the dynamic analogue of the von Karman large-deflection theory. Four sets of symmetrical boundary conditions are considered with the restriction of uniform pressure dynamic loads. The model takes the form of a mass on a cubic-hardening spring with each term defined by algebraic expressions of the plate parameters. The results for some specific problems are compared with two previous solutions. This method is less accurate but simpler to develop and apply.

Bayles, D. J.↗
DOE OSTI2021

Chemical Kinetics of the Autoxidation of Poly(ethylenimine) in CO 2 Sorbents

The oxidative degradation rates of a CO 2 sorbent composed of a mesoporous alumina impregnated with poly- (ethylenimine) (PEI) are measured under systematically varied conditions and a reaction rate law is created. Good agreement is shown between the rate of oxidation obtained via in situ calorimetric heat measurement during oxidative degradation reactions and the loss of CO 2 capture performance presented as amine efficiency (mol CO 2 /mol amine). PEI mass loss and elemental composition are tracked over the course of the reaction and used in conjunction with the oxidation rate measurements to shed insight into the oxidation reaction(s). These data, in combination with measurements of the heat of reaction, suggest a common reaction set across the range of temperatures, oxygen concentrations, and sorbent compositions tested. The data are consistent with the basic autoxidation scheme (BAS), the accepted mechanism of autoxidation of aliphatic polymers. We propose a lumped kinetic model to describe the oxidation reaction set and estimate an activation energy of 105 kJ/mol and an oxygen reaction order of 0.5–0.7 from the data accordingly. Furthermore, these parameters can be incorporated into process cycle models to estimate the material lifetime, a critical uncertainty in the deployment of DAC technologies.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Progress on the Reduced Gravity Cryogenic Transfer (RGCT) Project

Reduced gravity transfer of cryogenic propellants is crucial to being able to perform planned extended-duration space exploration missions. However, the transfer of cryogenic propellants under reduced gravity conditions has never been demonstrated in a mass-efficient fashion. Efficient cryogenic fluid transfer methods will reduce the transfer time or amount of propellant consumed for chilldown of transfer lines and tanks and ensure successful engine restart or fill of a customer receiver tank. The purpose of the Reduced Gravity Cryogenic Transfer (RGCT) project is to enhance line chilldown, tank chilldown, and tank fill/transfer in a reduced gravity environment through (1) ground and reduced gravity cryogenic testing and (2) numerical model development and validation, which includes empirical, lumped capacitance, and computational fluid dynamics modeling. Technologies developed, data gathered, and models developed and validated under RGCT have played a critical role in enabling longer duration in-space missions. This presentation will provide a description of the ongoing cryogenic propellant transfer ground and reduced gravity testing, numerical modeling, and technology development to-date.

Boiling↗
DOE OSTI2024

Simulation of gas mixture dynamics in a pipeline network using explicit staggered-grid discretization

Here we develop an explicit staggered finite difference discretization scheme for simulating the transport of highly heterogeneous gas mixtures through pipeline networks. This study is motivated by the proposed blending of hydrogen into natural gas pipelines to reduce end use carbon emissions while using existing pipeline systems throughout their planned lifetimes. Our computational method accommodates an arbitrary number of constituent gases with very different physical properties that may be injected into a network with significant spatiotemporal variation. In this setting, the gas flow physics are highly location- and time- dependent, so that local composition and nodal mixing must be accounted for. The resulting conservation laws are formulated in terms of pressure, partial densities and flows, and volumetric and mass fractions of the constituents. We include non-ideal equations of state that employ linear approximations of gas compressibility factors, so that the pressure dynamics propagate locally according to a variable wave speed that depends on mixture composition and density. We derive compatibility relationships for network edge boundary values that are more complex than for a homogeneous gas. The simulation method is evaluated on initial boundary value problems for a single pipe and a small network, is cross-validated with a lumped element simulation, and used to demonstrate a local monitoring and control policy for maintaining allowable concentration levels.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Modeling, Modal Properties, and Mesh Stiffness Variation Instabilities of Planetary Gears

Planetary gear noise and vibration are primary concerns in their applications in helicopters, automobiles, aircraft engines, heavy machinery and marine vehicles. Dynamic analysis is essential to the noise and vibration reduction. This work analytically investigates some critical issues and advances the understanding of planetary gear dynamics. A lumped-parameter model is built for the dynamic analysis of general planetary gears. The unique properties of the natural frequency spectra and vibration modes are rigorously characterized. These special structures apply for general planetary gears with cyclic symmetry and, in practically important case, systems with diametrically opposed planets. The special vibration properties are useful for subsequent research. Taking advantage of the derived modal properties, the natural frequency and vibration mode sensitivities to design parameters are investigated. The key parameters include mesh stiffnesses, support/bearing stiffnesses, component masses, moments of inertia, and operating speed. The eigen-sensitivities are expressed in simple, closed-form formulae associated with modal strain and kinetic energies. As disorders (e.g., mesh stiffness variation. manufacturing and assembling errors) disturb the cyclic symmetry of planetary gears, their effects on the free vibration properties are quantitatively examined. Well-defined veering rules are derived to identify dramatic changes of natural frequencies and vibration modes under parameter variations. The knowledge of free vibration properties, eigen-sensitivities, and veering rules provide important information to effectively tune the natural frequencies and optimize structural design to minimize noise and vibration. Parametric instabilities excited by mesh stiffness variations are analytically studied for multi-mesh gear systems. The discrepancies of previous studies on parametric instability of two-stage gear chains are clarified using perturbation and numerical methods. The operating conditions causing parametric instabilities are expressed in closed-form suitable for design guidance. Using the well-defined modal properties of planetary gears, the effects of mesh parameters on parametric instability are analytically identified. Simple formulae are obtained to suppress particular instabilities by adjusting contact ratios and mesh phasing.

Parker, Robert G.↗
NASA NTRS1996

Impeller leakage flow modeling for mechanical vibration control

HPOTP and HPFTP vibration test results have exhibited transient and steady characteristics which may be due to impeller leakage path (ILP) related forces. For example, an axial shift in the rotor could suddenly change the ILP clearances and lengths yielding dynamic coefficient and subsequent vibration changes. ILP models are more complicated than conventional-single component-annular seal models due to their radial flow component (coriolis and centrifugal acceleration), complex geometry (axial/radial clearance coupling), internal boundary (transition) flow conditions between mechanical components along the ILP and longer length, requiring moment as well as force coefficients. Flow coupling between mechanical components results from mass and energy conservation applied at their interfaces. Typical components along the ILP include an inlet seal, curved shroud, and an exit seal, which may be a stepped labyrinth type. Von Pragenau (MSFC) has modeled labyrinth seals as a series of plain annular seals for leakage and dynamic coefficient prediction. These multi-tooth components increase the total number of 'flow coupled' components in the ILP. Childs developed an analysis for an ILP consisting of a single, constant clearance shroud with an exit seal represented by a lumped flow-loss coefficient. This same geometry was later extended to include compressible flow. The objective of the current work is to: supply ILP leakage-force impedance-dynamic coefficient modeling software to MSFC engineers, base on incompressible/compressible bulk flow theory; design the software to model a generic geometry ILP described by a series of components lying along an arbitrarily directed path; validate the software by comparison to available test data, CFD and bulk models; and develop a hybrid CFD-bulk flow model of an ILP to improve modeling accuracy within practical run time constraints.

Palazzolo, Alan B.↗
DOE OSTI2024

Reduced-order condensed-phase kinetic models for polyethylene, polypropylene and polystyrene thermochemical recycling

Thermochemical recycling of plastic waste (PW) into chemicals and energy vectors requires coupling particle and reactor-scale simulations to accurate condensed phase pyrolysis mechanisms for each constituent. This work proposes a methodology to derive reduced-order condensed-phase kinetic models from validated semi-detailed kinetic mechanisms. Two types of kinetic models are obtained for polyethylene (PE), polypropylene (PP) and polystyrene (PS): reduced semi-detailed models and multi-step fully lumped ones. These families offer different compromises between accuracy and computational cost. The former employ 50–100 gas + liquid species and describe both the radical degradation and the detailed carbon distribution of the products. Conversely, the latter involves 5–10 species per polymer tracking only the main petroleum cuts. The kinetic mechanisms are complemented by the definition of thermochemical properties of gas, liquid, and solid-phase species, accounting for phase-transitions through pseudo-chemical reactions. Model validations are performed by comparison with experimental data and the original semi-detailed mechanisms in terms of mass loss, heat fluxes and product distribution profiles. The resulting CHEMKIN-like condensed-phase models are attached as Supplementary Material and as a GitHub repository. Extending the proposed approach to other polymers and coupling it with existing subsets in the CRECK kinetic framework (e.g., biomass, PVC, PET) offers a powerful tool to model thermochemical recycling of PW and biomass/PW mixtures.

kinetics↗
DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗
DOE OSTI2024

Development of a machine learning model for polyethylene pyrolysis using a detailed reaction mechanism

Waste plastics have recently received significant attention as the issue of waste generation continues to increase. Thermal conversion processes, such as pyrolysis and gasification, are attractive potential technologies for utilizing waste plastics and reducing overall waste generation. Efficient utilization of plastics requires a detailed understanding of the conversion process such as pyrolysis and gasification. However, a mechanistic understanding of these processes lead to large and complex kinetic schemes that are not suited for large-scale and long-time simulation methods. Currently, most modeling approaches for pyrolysis and gasification rely on globally lumped, simplified kinetic schemes that provide results that are classified by their product type and not individual species, which limit the level of fidelity achieved via modeling. A machine learning (ML) model has been developed for the primary reactions of high-density polyethylene (HDPE) in an attempt to increase computational efficiency while still maintaining a high level of detail and accuracy. The ML model is trained on a detailed reaction mechanism containing 42 total species and 737 chemical reactions. A DeepONet branch and trunk architecture was adopted to train the model using time-steps relevant to computational fluid dynamics simulations. The ML used physics-informed loss functions to ensure mass conservation. The surrogate model has been deployed in simple MFiX CFD simulations, single particle and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗
DOE OSTI2020

Gas Generation Models for Thermal Runaway in Lithium Ion Batteries

A numerical model is implemented to study cell venting, internal pressure, and gas-phase dynamics behavior of Li-ion cells undergoing thermal runaway. A k-ɛ Reynolds-Averaged Navier-Stokes (RANS) model is adopted to describe the turbulent flow out of the cells, while the fluid dynamics inside the cells is described by Darcy-Forchheimer’s equation. Thermal abuse reactions and gas generation kinetics are described by a single-step lumped reaction model. A series of computational fluid dynamics (CFD) simulations are conducted on a single cell at various states-of-charge (100%, 50%, 25%) to demonstrate detailed flow and thermal behavior as a function of quantity of gas generated during cell venting. Venting events are categorized into two stages: i) breaching of the cell container and ii) thermal runaway reactions. It is shown that the cell response is dominated by the second stage since most of the gases are generated during thermal runaway. Also, the propensity for propagation is highly affected by state-of-charge (SOC). Cells at higher SOCs produce more heat and gas during the venting event, owing to higher mass and concentrations of reacting gases, and consequently reach higher internal cell pressures which increase the risk of side-wall breaching.

Kim, Jinyong↗
DOE OSTI2021

Modeling cell venting and gas-phase reactions in 18650 lithium ion batteries during thermal runaway

A numerical model is developed to study cell venting, internal pressure, and gas-phase dynamics behavior of 18650 Li-ion cells undergoing thermal runaway. A k-e Reynolds-Averaged Navier-Stokes (RANS) model is adopted to describe the turbulent flow out of the cells, while the fluid dynamics inside the cells is described by Darcy-Forchheimer's equation. Thermal abuse reactions and gas generation kinetics are described by a single-step lumped reaction model. Then, a series of computational fluid dynamics (CFD) simulations are conducted on a single 18650 cell at various states-of-charge (100%, 50%, 25%) to study detailed flow and thermal behavior as a function of quantity of gas generated during cell venting. Venting events are categorized into two stages: i) breaching of the cell container and ii) thermal runaway reactions. It is found that the cell response is dominated by the second stage since most of the gases are generated during thermal runaway. Also, the propensity for propagation is highly affected by state-of-charge (SOC). Cells at higher SOCs produce more heat and gas during the venting event, owing to higher mass and concentrations of reacting gases, and consequently reach higher internal cell pressures which increase the risk of side-wall breaching.

25 ENERGY STORAGE↗
DOE OSTI2022

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗