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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Maximising the investment returns of a grid‐connected battery considering degradation cost

Energy storage systems (ESSs) are being deployed widely due to numerous benefits including operational flexibility, high ramping capability, and decreasing costs. This study investigates the economic benefits provided by battery ESSs when they are deployed for market‐related applications, considering the battery degradation cost. A comprehensive investment planning framework is presented, which estimates the maximum revenue that the ESS can generate over its lifetime and provides the necessary tools to investors for aiding the decision making process regarding an ESS project. The applications chosen for this study are energy arbitrage and frequency regulation. Lithium‐ion batteries are considered due to their wide popularity arising from high efficiency, high energy density, and declining costs. A new degradation cost model based on energy throughput and cycle count is developed for Lithium‐ion batteries participating in electricity markets. The lifetime revenue of ESS is calculated considering battery degradation and a cost–benefit analysis is performed to provide investors with an estimate of the net present value, return on investment and payback period. The effect of considering the degradation cost on the estimated revenue is also studied. The proposed approach is demonstrated on the IEEE Reliability Test System and historical data from PJM Interconnection.

25 ENERGY STORAGE↗
DOE OSTI2021

Numerical Simulations of Time-Resolved Photoluminescence in CdSexTe1-x/CdTe Solar Cells

We present initial time-resolved photoluminescence (TRPL) simulations in graded CdSexTe1-e thin-film solar cells to quantify the front-interface recombination velocity, S int,front . Our model includes several composition dependences: bandgap energy, absorption coefficient, electron affinity, and carrier lifetime. Cathodoluminescence spectrum imaging measurements on bevels provide an estimate of the bandgap and the CdSe x Te 1-x alloy composition through the absorber thickness. TRPL decays are simulated as a function of the laser power, S int,front , front-interface band offset, and bulk Shockley-Read-Hall lifetime. We find the impact of S intf,ront on the PL decay increases as the band offset shifts from a "spike" to a "cliff". Recombination rate analysis shows that back-interface recombination could potentially dictate the later part of the TRPL decay "t 2" in high-lifetime CdSe x Te 1-x cells. We briefly discuss ongoing work to determine TRPL measurement conditions that maximize sensitivity to S itnt,front.

CdTe solar cells↗
DOE OSTI2023

Effects of finite sampling on fatigue damage estimation of wind turbine components: A statistical study

The variability of the wind turbine loads complicates fatigue assessment in the design phase, as performing simulations covering the entire lifetime is computationally expensive. The current work provides important information for assessing the uncertainty in fatigue damage estimation due to finite data. Here we study the sample size effect on mean, variance, and skewness of damage in each wind bin, identify the important wind bins, and study the uncertainty propagation from each wind bin to the lifetime damage using 3600 aeroelastic simulations and bootstrapping. To achieve less than 1% error in the damage estimation across all load channels in the current case study, at least 100 turbulence seeds are needed. Damage in different wind bins follows a lognormal distribution when using the conventional approach of six seeds. The provided insights and information allow the designer to achieve a specific level of accuracy for a given computational cost using strategic bin sampling.

17 WIND ENERGY↗
DOE OSTI2020

Optimization-Based Fast-Frequency Estimation and Control of Low-Inertia Microgrids

The lack of inertial response from non-synchronous, inverter-based generation in microgrids makes the power system vulnerable to a large rate of change of frequency (ROCOF) and frequency excursions. Energy storage systems (ESSs) can be utilized to provide fast-frequency support to prevent such large excursions in the system. However, fast-frequency support is a power-intensive application that has a significant impact on the ESS lifetime. In this paper, a framework that allows the ESS operator to provide fast-frequency support as a service is proposed. The framework maintains the desired quality-of-service (limiting the ROCOF and frequency) while taking into account the ESS lifetime and physical limits. The framework utilizes moving horizon estimation (MHE) to estimate the frequency deviation and ROCOF from noisy phase-locked loop (PLL) measurements. These estimates are employed by a model predictive control (MPC) algorithm that computes control actions by solving a finite-horizon, online optimization problem. Additionally, this approach avoids oscillatory behavior induced by delays that are common when using low-pass filters as with traditional derivative-based (virtual inertia) controllers. MATLAB/Simulink simulations on a test system from Cordova, Alaska, show the effectiveness of the MHE-MPC approach to reduce frequency deviations and ROCOF of a low-inertia microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗
DOE OSTI2024

Sensitivity analysis, surrogate modeling, and optimization of pebble-bed reactors considering normal and accident conditions

This research provides a valuable tool that streamlines the optimization process while significantly increasing its accuracy. This study creates a robust framework for reactor design optimization by incorporating comprehensive modeling using the Comprehensive Reactor Analysis Bundle, or BlueCRAB, within the Multiphysics Object-Oriented Simulation Environment (MOOSE). BlueCRAB is the United States Nuclear Regulatory Commission's code suite for non-light water reactor analysis and includes the Griffin, Pronghorn, and Bison applications. This not only improves the efficiency of the optimization process but also enhances the reliability of the results. Such a tool is essential for advancing the state-of-the-art in pebble-bed reactor technology and is critical for achieving the goals of Generation IV reactors, which aim for safe, sustainable, and economically viable nuclear energy solutions. This work presents and applies this workflow on pebble-bed reactors while considering both normal and off-normal conditions. A representative gas-cooled pebble-bed reactor at equilibrium core conditions serves as the nominal design specification for normal operation and is based on previous research. The depressurized loss-of-forced-cooling accident is deployed for off-normal conditions in this work. After defining design-related parameters and quantities of interest regarding reactor safety and performance, this multiphysics model is sampled using the MOOSE stochastic tools module. The result is a comprehensive dataset of configurations, enabling sensitivity analysis and the generation of surrogate models. Subsequently, the dataset and surrogate models are employed in two optimization studies aimed at maximizing fuel utilization and economic profit while adhering to safety and operational constraints. Performing the optimization process with fuel utilization as the metric leads to an improvement of approximately 10%, compared to engineering-judgment-based nominal conditions. The optimization on economic profit leads to an estimated increase of ~300 million USD over the lifetime of the reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimizing radar scan strategies for tracking isolated deep convection using observing system simulation experiments

Abstract. Optimizing radar observation strategies is one of the most important considerations in pre-field campaign periods. This is especially true for isolated convective clouds that typically evolve faster than the observations captured by operational radar networks. This study investigates uncertainties in radar observations of the evolution of the microphysical and dynamical properties of isolated deep convective clouds developing in clean and polluted environments. It aims to optimize the radar observation strategy for deep convection through the use of high-spatiotemporal cloud-resolving model simulations, which resolve the evolution of individual convective cells every 1 min, coupled with a radar simulator and a cell tracking algorithm. The radar simulation settings are based on the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field campaigns held in the Houston, TX, area but are generalizable to other field campaigns focusing on isolated deep convection. Our analysis produces the following four outcomes. First, a 5–7 m s−1 median difference in maximum updrafts of tracked cells is shown between the clean and polluted simulations in the early stages of the cloud lifetimes. This demonstrates the importance of obtaining accurate estimates of vertical velocity from observations if aerosol impacts are to be properly resolved. Second, tracking of individual cells and using vertical cross section scanning every minute capture the evolution of precipitation particle number concentration and size represented by polarimetric observables better than the operational radar observations that update the volume scan every 5 min. This approach also improves multi-Doppler radar updraft retrievals above 5 km above ground level for regions with updraft velocities greater than 10 m s−1. Third, we propose an optimized strategy composed of cell tracking by quick (1–2 min) vertical cross section scans from more than one radar in addition to the operational volume scans. We also propose the use of a single-RHI (range height indicator) updraft retrieval technique for cells close to the radars, for which multi-Doppler radar retrievals are still challenging. Finally, increasing the number of deep convective cells sampled by such observations better represents the median maximum updraft evolution with sample sizes of more than 10 deep cells, which decreases the error associated with sampling the true population to less than 3 m s−1.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Water dissociation at the water–rutile TiO 2 (110) interface from ab initio-based deep neural network simulations

The interaction of water with TiO 2 surfaces is of crucial importance in various scientific fields and applications, from photocatalysis for hydrogen production and the photooxidation of organic pollutants to self-cleaning surfaces and bio-medical devices. In particular, the equilibrium fraction of water dissociation at the TiO 2 –water interface has a critical role in the surface chemistry of TiO 2 , but is difficult to determine both experimentally and computationally. Among TiO 2 surfaces, rutile TiO 2 (110) is of special interest as the most abundant surface of TiO 2 ’s stable rutile phase. While surface-science studies have provided detailed information on the interaction of rutile TiO 2 (110) with gas-phase water, much less is known about the TiO 2 (110)–water interface, which is more relevant to many applications. In this work, we characterize the structure of the aqueous TiO 2 (110) interface using nanosecond timescale molecular dynamics simulations with ab initio-based deep neural network potentials that accurately describe water/TiO 2 (110) interactions over a wide range of water coverages. Simulations on TiO 2 (110) slab models of increasing thickness provide insight into the dynamic equilibrium between molecular and dissociated adsorbed water at the interface and allow us to obtain a reliable estimate of the equilibrium fraction of water dissociation. We find a dissociation fraction of 22 ± 6% with an associated average hydroxyl lifetime of 7.6 ± 1.8 ns. These quantities are both much larger than corresponding estimates for the aqueous anatase TiO 2 (101) interface, consistent with the higher water photooxidation activity that is observed for rutile relative to anatase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]

This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.

Branlard, Emmanuel↗
DOE OSTI2022

Large-Area (Ag,Cu)(In,Ga)Se 2 Thin-Film Solar Cells with Increased Bandgap and Reduced Voltage Losses Realized with Bulk Defect Reduction and Front-Grading of the Absorber Bandgap

The 1.24 eV bandgap, 18.8% power conversion efficiency Ag-alloyed chalcopyrite (Ag,Cu)(In,Ga)Se 2 (ACIGS) solar cells are characterized to relate voltage and efficiency improvements to electro-optical (EO) characteristics. Shockley-Read-Hall recombination center defect density, identified and characterized through deep level transient spectroscopy and time-resolved photoluminescence (TRPL), is reduced through potassium and copper treatment optimization. Concomitantly, longer minority carrier lifetimes are achieved, which increases open-circuit voltage (V OC ). Near-conduction band defects associated in earlier studies with light-induced current instability are also mitigated. Analysis of charge-carrier dynamics after single- and two-photon excitation is used to separate recombination at the front interface and in the absorber bulk. From TRPL decay simulations, the authors estimate ranges of key solar cell material characteristics: bulk carrier lifetime T bulk = 110-210 ns, charge-carrier mobility u = 110-160 cm 2 V -1 s -1 , and front interface recombination velocity S front = 700-1050 cm s -1 . This lowest-reported S front for ACIGS absorbers originates from the notched conduction band grading, which also makes the impact of the back interface recombination negligible. It is suggested in the results that solar cell performance enhancements can be made most readily with two distinct strategies: improving device architecture and reducing semiconductor defect densities. Using these approaches, power conversion efficiency in large-area solar cells is improved by 1.1% absolute.

14 SOLAR ENERGY↗
DOE OSTI2024

Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability

Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Quantification and evaluation of strain reduction from small-bubble gas injection in Spallation Neutron Source target vessels

Small-bubble gas injection has been routinely utilized in the operation of Spallation Neutron Source (SNS) mercury targets since 2017 to mitigate cavitation-induced erosion damage to target vessels. Strain measurements of target vessels collected in-situ during initial operation with gas injection were used to study the gas injection effect on the structural response of targets to proton pulses. A significant strain reduction owing to gas injection was found by comparing the strain measurement data during operation with and without gas injection. The research presented here focuses on quantifying strain reductions in SNS targets and evaluating the effect of small-bubble gas injection by comparing different bubbler types and target designs. The strain measurement results show the gas injection significantly reduced strain in SNS target vessels; strain values decreased by 30% to 80% for targets operating with gas injection. Stress and strain responses of SNS targets were simulated to numerically evaluate the gas injection effect. Based on the predicted stresses with and without gas injection, the fatigue lifetimes of SNS jet-flow design target were estimated using fe-safe fatigue analysis software. The simulations show these reductions should improve the fatigue life of target vessels and allow SNS targets to meet their fatigue design goal.

Fatigue life estimation↗
DOE OSTI2024

Iron dopant energy levels in β-Ga 2 O 3

The energetic positions of the two Fe dopant levels in the bandgap of β-Ga 2 O 3 are determined to be at 3.05(±0.05) and 3.85(±0.05) eV below the conduction band minimum from transmission measurements employing a sub-picosecond tunable ultraviolet laser radiation source. A further measurement of the quantum efficiency of photoelectron emission from the Fe:Ga 2 O 3 (010) photocathode is consistent with the obtained absorption data and a dominant optical phonon assisted Franck–Condon emission mechanism, while also providing an estimate of 100 ps for the conduction band electron lifetime.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

The 2025 Evaluation of Experimental Thermonuclear Reaction Rates (ETR25)

This work describes the formalism for estimating thermonuclear reaction rates for astrophysical applications, emphasizing modern statistical approaches such as Monte Carlo sampling and Bayesian models. We discuss related topics including the calculation of resonance energies from nuclear Q values, indirect estimates of particle partial widths, and matching of reaction rates at elevated temperatures to statistical model results. We have evaluated available experimental data on cross sections, resonance energies and strengths, partial widths, lifetimes, spin-parities, and spectroscopic factors. Based on these results, we have estimated numerical values of 78 experimental charged-particle thermonuclear reaction rates for target nuclei in the A = 2–40 mass region, for temperatures ranging from 1 MK to 10 GK. For each reaction, three rate values are provided: low, median, and high, corresponding to the 16th, 50th, and 84th percentiles, respectively, of the cumulative reaction rate probability density distribution. Additionally, we present the factor uncertainty of each rate at each temperature grid point. These results enable users to sample the reaction rate probability density in nucleosynthesis calculations, facilitating uncertainty estimates of nuclidic abundances. The rates presented here refer to their laboratory values. For use in stellar model simulations, these values need to be corrected for the effects of thermal excitations of the interacting nuclei. For each reaction, we include graphs that illustrate the fractional contributions to the overall reaction rate along with the associated uncertainty. These visuals are designed to assist both stellar modelers and nuclear experimentalists by identifying the primary sources of rate uncertain=^texttx);ty at specific stellar temperatures. A graphical comparison with earlier Monte Carlo rates is also provided.

Nuclear astrophysics↗
DOE OSTI2024

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗
DOE OSTI2023

Carrier Recombination Dynamics of Surface-Passivated Epitaxial (100)Ge, (110)Ge, and (111)Ge Layers by Atomic Layer Deposited Al2O3

Germanium (Ge) and its heterostructures with compound semiconductors offer a unique optoelectronic functionality due to its pseudo-bandgap nature, that can be transformed to a direct bandgap material by providing strain and/or mixing with tin. Moreover, two crystal surfaces, (100)Ge and (110)Ge, that are technologically important for ultralow power fin or nanosheet transistors, could offer unprecedented properties with reduced surface defects after passivating these surfaces by atomic layer deposited (ALD) dielectrics. In this work, the crystallographically oriented epitaxial Ge/AlAs heterostructures were grown and passivated with ALD Al2O3 dielectrics, and the microwave photoconductive decay (u-PCD) technique was employed to evaluate carrier lifetimes at room temperature. The X-ray photoelectron spectroscopy analysis reveals no role of orientation effect in the quality of the ALD Al2O3 dielectric on oriented Ge layers. The carrier lifetimes measured using the u-PCD technique were benchmarked against unpassivated Ge/AlAs heterostructures. Excitation wavelengths of 1500 and 1800 nm with an estimated injection level of ~10^13 cm-3 were selected to measure the orientation-specific carrier lifetimes. The carrier lifetime was increased from 390 ns to 565 ns for (100)Ge and from 260 ns to 440 ns for (110)Ge orientations with passivation, whereas the carrier lifetime is almost unchanged for (111)Ge after passivation. This behavior indicates a strong dependence of the measured lifetime on surface orientation and surface passivation. The observed increase (>1.5x) in lifetime with Al2O3-passivated (100)Ge and (110)Ge surfaces is due to the lower surface recombination velocity compared to unpassivated Ge/AlAs heterostructures. The enhancement of carrier lifetime from passivated Ge/AlAs heterostructures with (100)Ge and (110)Ge surface orientations offers a path for the development of nanoscale transistors due to the reduced interface state density.

Al2O3↗
DOE OSTI2021

Experimental 3-dimensional tracking of the dynamics of a single electron in the Fermilab Integrable Optics Test Accelerator (IOTA)

We present the results of experimental studies on the transverse and longitudinal dynamics of a single electron in the IOTA storage ring. IOTA is a flexible machine dedicated to beam physics experiments with electrons and protons. A method was developed to reliably inject and circulate a controlled number of electrons in the ring. A key beam diagnostic system is the set of sensitive high-resolution digital cameras for the detection of synchrotron light emitted by the electrons. With 60–130 electrons in the machine, we measured beam lifetime and derived an absolute calibration of the optical system. At exposure times of 0.5 s, the cameras were sensitive to individual electrons. Camera images were used to reconstruct the time evolution of oscillation amplitudes of a single electron in all 3 degrees of freedom. The evolution of amplitudes directly showed the interplay between synchrotron-radiation damping, quantum excitations, and scattering with the residual gas. From the distribution of measured single-electron oscillation amplitudes, we deduced transverse emittances, momentum spread, damping times, and beam energy. Estimates of residual-gas density and composition were calculated from the measured distributions of vertical scattering angles. Combining scattering and lifetime data, we also provide an estimate of the aperture of the ring. To our knowledge, this is the first time that the dynamics of a single electron are tracked in all three dimensions with digital cameras in a storage ring.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Benefits of colorectal cancer screening using fecal immunochemical testing with varying positivity thresholds by age and sex

Background Fecal immunochemical test (FIT) performance for colorectal cancer screening varies by age and sex, yet most FIT-based screening programs use uniform positivity thresholds. This study assessed the potential benefits of stratifying FIT thresholds based on age and sex. Methods We conducted a meta-analysis of FIT sensitivity and specificity at various positivity thresholds by age and sex. We then used these estimates in 2 microsimulation models of colorectal cancer and projected lifetime clinical outcomes, incremental costs, and quality-adjusted life-years (QALYs) gained from age- and sex-stratified FIT strategies. FIT thresholds ranged from 10 to 50 µg hemoglobin per gram of feces. Results For current uniform FIT screening (20 µg hemoglobin/gram of feces), models projected 85.67 to 122.15 QALYs gained at incremental costs of ‒$982 to $504 per 1000 individuals compared with no screening. At equivalent costs to current uniform screening, only 1 model found stratified FIT approaches cost-effective, yielding a marginal increase of 1.04 and 1.10 QALYs gained/1000 female and male individuals, respectively. At a willingness-to-pay threshold of $100 000/QALYs gained, both models found stratified FIT cutoffs to be the best strategy, with cutoffs being equal to or higher for males and lowest at older ages (70-75 years). Uniform strategies showed comparable effectiveness, falling within 1 quality-adjusted life-day per person of efficient strategies at up to $112 more per person. Results were sensitive to FIT test performance characteristics and 1-time setup costs. Conclusion Stratifying FIT thresholds by age and sex may be cost-effective compared to current screening. The gain in expected health benefits with stratified FIT screening, however, is likely small.

Harlass, Matthias↗