Simulation Project Research Articles

A model for quantification of environmental risk in mining ventures

The premature termination of industrial projects, often triggered by insufficient revenue generation to cover liabilities, poses a significant challenge in project evaluation. Although the conventional discounted cash flow (DCF) method remains widely used, its inability to account for project failure probabilities can lead to resource misallocation. This study aims to address this limitation by applying real options theory to assess the risk of premature abandonment within the context of a mineral extraction project. In this proposed system, fluctuations in environmental remediation costs are modelled by considering the cumulative probabilities of cost increases or decreases at each time step. The simulated project value reflects the cumulative activities required for mine closure, where each ton of extracted ore generates an environmental liability demanding remediation. Through the application of this system, the study demonstrates its effectiveness in identifying an escalating probability of project closure over time. Particularly, the findings reveal the existence of a critical threshold date. Beyond this date, any operational suspension exceeding one year renders project closure the economically optimal choice. This closure encompasses all necessary environmental restoration activities. By integrating real options theory into project evaluation, this study offers a more comprehensive approach to assessing the risk of premature project abandonment in mineral extraction projects. Through the consideration of fluctuating environmental remediation costs and the cumulative probabilities of project closure, it provides valuable insights for decision-making in project management and resource allocation. The trigger curve generated allowed for the identification of the viability threshold of the venture. Identifying the threshold to initiate the mining closure project.

PERFORMANCE INVESTIGATION OF A 5 MW PHOTOVOLTAIC SYSTEM: ALFASHIR SUDAN

This study comprehensively analyzes the operational performance and economic feasibility of a 5MW grid-connected photovoltaic in Sudan over a two-year monitoring period. Leveraging the capabilities of PVSyst software, the actual plant performance was rigorously compared to simulation predictions. Results revealed a significant disparity between observed and simulated energy generation, prompting the exploration of potential areas for enhancement. Seasonal fluctuations in the performance ratio were evident, with peak values during some seasons, albeit not consistently aligning with simulation projections. Despite these challenges, the Plant made a notable impact by reducing CO2 emissions, highlighting the environmental benefits of solar energy. Financial analysis unveiled discrepancies between actual and simulated savings, underscoring the need for optimization and efficiency improvements. The equity payback period, influenced by electricity pricing policies, was estimated at 15 years, emphasizing its role in assessing project economics. The region's high radiation intensity and humidity levels emerged as significant factors affecting plant performance. Addressing these challenges is crucial for maximizing the PV plant's operational efficiency and viability. Our Recommendations include thoroughly examining control system functions during commissioning and improving operational accuracy.

Applying Human Factors and Systems Simulation Methods to Inform a Multimillion-Dollar Healthcare Decision.

This article describes a case study of a collaborative human factors (HF) and systems-focused simulation (SFS) project to evaluate potential patient and staff safety risks associated with a multimillion-dollar design and construction decision. The combined integration of HF and SFS methods in healthcare related to testing and informing the design of new environments and processes is underutilized. Few realize the effectiveness of this integration in healthcare to reduce risk and improve decision-making, safety, design, efficiency, patient experience, and outcomes. This project showcases how the combined use of HF and SFS methods can provide objective evidence to help inform decisions. The project was initiated by a healthcare executive team looking for an objective, user informed analysis of a current connector passageway between two existing buildings. The goal was to understand the implications of keeping the current route for simultaneous use for public and patients service flow versus building and financing a new passageway for separate flow and transport. An interprofessional team of intensive care unit professionals participated in two simulations designed to test the current connector. A failure mode and effects analysis and qualitative debrief feedback was used to evaluate risks and potential failures. The evaluation resulted in data that enabled informed executive decision making for the most effective, efficient, and safest option for public, staff, and patient transport between two buildings. This evaluation resulted in the decision to go forward with building a multimillion-dollar new connector passageway to improve integrated care and transport.

A Conceptual Framework for Immersive Acoustic Auralisation: Investigating the Key Attributes

In architectural acoustics, the assessment of sound propagation in interior and/or environmental conditions has now become progressively more prominent throughout the past few decades, as a response to the development of advanced prediction tools. Within the adaptation of virtual reality (VR) systems, it is necessary to considerably expedite the prediction and simulation software as well as to enable flexible and responsive data analysis during simulation and 3D audio sensory projection. To generate ideal immersion in a simulated virtual environment, the generated stimulus across all senses should therefore be coherent. Accordingly, in the domain of acoustic in virtual reality, the system sound simulation must be constructed efficiently in order to convey the auditory stimuli to the user in an appropriate manner. This necessitates the implementation of virtual reality system as an advanced prediction tool that can accurately anticipate and replicate realistic audio experiences. Therefore, this study explores the realm of acoustic virtual reality (AVR) through a critical review with the purpose of elucidating design attributes and determining factors in generating immersive acoustic VR experiences. In light of these findings, the aim of this paper is to develop a comprehensive conceptual framework that will serve as a beneficial guide and road map for future researchers and developers in the field.

Impact of cone-beam computed tomography artifacts on dose calculation accuracy for lung cancer.

To implement image-guided adaptive radiotherapy (IGART), many studies investigated dose calculations on cone-beam computed tomography (CBCT). A high HU accuracy is crucial for a high dose calculation accuracy and many imaging sites showed satisfactory results. It has been shown that the dose calculation accuracy for lung cancer lags behind. To examine why the dose calculation accuracy for lung is insufficient, the relative effects of the field-of-view (FOV), breathing motion, and scatter on dose calculation accuracy were studied. A framework was built to simulate CBCT scans for lung cancer patients by forward projecting repeat CT (rCT) scans for two scan geometries: small (SFOV) and medium FOV (MFOV). Breathing motion was modeled by applying a 4D deformation vector field to the mid-position rCT. Scatter was modeled by Monte-Carlo simulations with/without an anti-scatter grid (ASG). Simulated projections were reconstructed using filtered back-projection with/without scatter correction. In case of the SFOV, the CBCT images were patched with the planning CT scan in axial direction. The treatment plan was recalculated on the rCT and simulated CBCT. The mean Hounsfield unit (HU) difference (ΔHUmean), the structural similarity index measure (SSIM), and γ metrics were calculated for the CBCT datasets of various imaging settings. The differences in HU, SSIM and dose calculation accuracy for CBCTs with and without breathing motion were negligible (mean ΔHUmean=6.4vs. 13.7, mean SSIM=0.941vs. 0.957, mean γ (ref=MFOV)=0.75). The SFOV resulted in a lower HU (mean ΔHUmean=-9.2vs. 13.7) and SSIM (mean SSIM=0.912vs. 0.957), and therefore in dose differences compared to the MFOV (mean γ=1.22). Scatter led to considerable discrepancies in all metrics. Adding only the ASG improved the results more than only applying a scatter correction algorithm. Combining ASG and scatter correction algorithm resulted in an even higher dose calculation accuracy. Scatter and FOV are the main contributors to dose inaccuracies and motion has only a minor effect on dose calculation accuracy. Therefore, utilizing an appropriate scatter correction and FOV is important to achieve sufficient dose calculation accuracy to facilitate IGART for lung.

Reducing image artifacts in sparse projection CT using conditional generative adversarial networks

Reducing the amount of projection data in computed tomography (CT), specifically sparse-view CT, can reduce exposure dose; however, image artifacts can occur. We quantitatively evaluated the effects of conditional generative adversarial networks (CGAN) on image quality restoration for sparse-view CT using simulated sparse projection images and compared them with autoencoder (AE) and U-Net models. The AE, U-Net, and CGAN models were trained using pairs of artifacts and original images; 90% of patient cases were used for training and the remaining for evaluation. Restoration of CT values was evaluated using mean error (ME) and mean absolute error (MAE). The image quality was evaluated using structural image similarity (SSIM) and peak signal-to-noise ratio (PSNR). Image quality improved in all sparse projection data; however, slight deformation in tumor and spine regions was observed, with a dispersed projection of over 5°. Some hallucination regions were observed in the CGAN results. Image resolution decreased, and blurring occurred in AE and U-Net; therefore, large deviations in ME and MAE were observed in lung and air regions, and the SSIM and PSNR results were degraded. The CGAN model achieved accurate CT value restoration and improved SSIM and PSNR compared to AE and U-Net models.

Simulation in engineering education: The transition from physical experimentation to digital immersive simulated environments

Besides its use as a powerful systems analysis tool, simulation has also been used for decades in educational settings as a teaching and learning method. Simulation can replace or augment real-world inquiry-based experiences by providing learners with a low-cost and risk-free experimentation platform to develop knowledge and skills in a simulated environment. This paper presents an overview of current applications and the ongoing transition from physical experimentation to digital simulations and immersive simulated learning environments in engineering education. The paper highlights major implementation and research gaps related to simulation-based learning and immersive simulated learning environments, namely, lack of integration with learning theories and limited formal assessments of effectiveness. Potential implementation approaches and important areas for future educational research are discussed and exemplified in response to the identified gaps. The discussions presented are intended for simulationists, educational researchers, and instructors who are interested in designing and/or utilizing engineering education interventions involving simulated learning environments and immersive technologies in their teaching and educational research. In particular, the Immersive Simulation-Based Learning (ISBL) approach discussed in the paper provides a framework for simulationists to reuse the models developed as part of their simulation projects for educational purposes.

Development and tuning of models for accurate simulation of CT spatial resolution using CatSim.

Objective. We sought to systematically evaluate CatSim's ability to accurately simulate the spatial resolution produced by a typical 64-detector-row clinical CT scanner in the projection and image domains, over the range of clinically used x-ray techniques.Approach.Using a 64-detector-row clinical scanner, we scanned two phantoms designed to evaluate spatial resolution in the projection and image domains. These empirical scans were performed over the standard clinically used range of x-ray techniques (kV, and mA). We extracted projection data from the scanner, and we reconstructed images. For the CatSim simulations, we developed digital phantoms to represent the phantoms used in the empirical scans. We developed a new, realistic model for the x-ray source focal spot, and we empirically tuned a published model for the x-ray detector temporal response. We applied these phantoms and models to simulate scans equivalent to the empirical scans, and we reconstructed the simulated projections using the same methods used for the empirical scans. For the empirical and simulated scans, we qualitatively and quantitatively compared the projection-domain and image-domain point-spread functions (PSFs) as well as the image-domain modulation transfer functions. We reported four quantitative metrics and the percent error between the empirical and simulated results.Main Results.Qualitatively, the PSFs matched well in both the projection and image domains. Quantitatively, all four metrics generally agreed well, with most of the average errors substantially less than 5% for all x-ray techniques. Although the errors tended to increase with decreasing kV, we found that the CatSim simulations agreed with the empirical scans within limits required for the anticipated applications of CatSim.Significance.The new focal spot model and the new detector temporal response model are significant contributions to CatSim because they enabled achieving the desired level of agreement between empirical and simulated results. With these new models and this validation, CatSim users can be confident that the spatial resolution represented by simulations faithfully represents results that would be obtained by a real scanner, within reasonable, known limits. Furthermore, users of CatSim can vary parameters including but not limited to system geometry, focal spot size/shape and detector parameters, beyond the values available in physical scanners, and be confident in the results. Therefore, CatSim can be used to explore new hardware designs as well as new scanning and reconstruction methods, thus enabling acceleration of improved CT scan capabilities.

The contribution of massive haloes to the matter power spectrum in the presence of AGN feedback

ABSTRACT The clustering of matter, as measured by the matter power spectrum, informs us about cosmology, dark matter, and baryonic effects on the distribution of matter in the universe. Using cosmological hydrodynamical simulations from the cosmo-OWLS and BAHAMAS simulation projects, we investigate the contribution of power in haloes with various masses, to the full power spectrum, as well as the power ratio between baryonic and dark matter only (DMO) simulations for a matched (between simulations) and an unmatched set of haloes. We find that the presence of AGN feedback suppresses the power on all scales for haloes of all masses examined (1011.25 ≤ M500, crit ≤ $10^{14.75}\, \mathrm{M_\odot }/h$), by ejecting matter from within $r_{500,\mathrm{c}}\,$ to $r_{200,\mathrm{m}}\,$ and potentially beyond in massive haloes (M500, crit ≳ $10^{{13}}\, \mathrm{M_\odot }/h$), and likely impeding the growth of lower-mass haloes as a consequence. A lower AGN feedback temperature changes the behaviour of high-mass haloes (M500, crit ≥ $10^{{13.25}}\, \mathrm{M_\odot }/h$), damping the effects of AGN feedback at small scales, $k\, {{\gtrsim }}\, {{4}}\, h\mathrm{\, Mpc^{-1}}$. For $k\, {{\lesssim }}\, {{3}}\, h\mathrm{\, Mpc^{-1}}$, group-sized haloes ($10^{{14\pm 0.25}}\, \mathrm{M_\odot }/h$) dominate the power spectrum, while on smaller scales the combined contributions of lower-mass haloes to the full power spectrum rise above that of the group-sized haloes. Finally, we present a model for the power suppression due to feedback, which combines observed mean halo baryon fractions with halo mass fractions and halo-matter cross-spectra extracted from DMO simulations to predict the power suppression to per cent level accuracy down to $k\, {{\approx }}\, {{10}}\, h\mathrm{\, Mpc^{-1}}$ without any free parameters.

Enhancement of Stopping Power Ratio (SPR) Estimation Accuracy through Image-Domain Dual-Energy Computer Tomography for Pencil Beam Scanning System: A Simulation Study.

Our study aims to quantify the impact of spectral separation on achieved theoretical prediction accuracy of proton-stopping power when the volume discrepancy between calibration phantom and scanned object is observed. Such discrepancy can be commonly seen in our CSI pediatric patients. One of the representative image-domain DECT models is employed on a virtual phantom to derive electron density and effective atomic number for a total of 34 ICRU standard human tissues. The spectral pairs used in this study are 90 kVp/140 kVp, without and with 0.1 mm to 0.5 mm additional tin filter. The two DECT images are reconstructed via a conventional filtered back projection algorithm (FBP) on simulated noiseless projection data. The best-predicted accuracy occurs at a spectral pair of 90 kVp/140 kVp with a 0.3 mm tin filter, and the root-mean-squared average error is 0.12% for tissue substitutes. The results reveal that the selected image-domain model is sensitive to spectral pair deviation when there is a discrepancy between calibration and scanning conditions. This study suggests that an optimization process may be needed for clinically available DECT scanners to yield the best proton-stopping power estimation.

The offshore wind speed changes in China: an insight into CMIP6 model simulation and future projections

Offshore wind speed in China plays a key role in affecting air–sea interactions, coastal tides, and wind energy, but its changes in a warming climate and the associated causes remain unclear. Based on the ERA5 reanalysis and the Coupled Model Intercomparison Project Phase 6 (CMIP6) models, this study evaluates the past and future variations of wind speed at 10 m (WS10) over China’s offshore seas in summer and winter. The results show that the CMIP6 multi-model mean performs well in simulating the climatological patterns (1981–2010) of WS10 for both seasons. The trends and leading variabilities in WS10 are also reasonably reproduced in the South China Sea (SCS). In the northern SCS, WS10 has strengthened during both seasons in the recent decades. In contrast, in the East China Sea (ECS), WS10 has increased (decreased) during summer (winter). Further attribution analysis suggests that the forcing of greenhouse gasses (aerosols) may make WS10 stronger (weaker) in the two seas and for both seasons, while natural variability tends to slow down (speed up) WS10 in the SCS and ECS during summer (winter). In addition, according to the CMIP6 model projections under various warming scenarios, WS10 is likely to increase over both the northern SCS and the ECS in summer, while WS10 will increase over the northern SCS but decrease over the ECS in winter. Differences in the projected WS10 changes in the ECS during summer and winter are attributed to the projected intensification (weakening) of the East Asian summer (winter) monsoon circulation.

A non-local total generalized variation regularization reconstruction method for sparse-view x-ray CT

Sparse-view x-ray computed tomography (CT) reconstruction, employing total generalized variation (TGV), effectively mitigates the stepwise artifacts associated with total variation (TV) regularization while preserving structural features within transitional regions of the reconstructed image. Despite TGV surpassing TV in reconstruction quality, it neglects the non-local self-similarity prior, recognized for its efficacy in restoring details during CT reconstruction. This study introduces a non-local TGV (NLTGV) to address the limitation of TGV regularization method. Specifically, we propose an NLTGV-regularized method for sparse-view CT reconstruction, utilizing non-local high-order derivative information to maintain image features and non-local self-similarity for detail recovery. Owing to the non-differentiability of the NLTGV regularized, we employ an alternating direction method of multipliers optimization method, facilitating an efficient solution by decomposing the reconstruction model into sub-problems. The proposed method undergoes evaluation using both simulated and real-world projection data. Simulation and experimental results demonstrate the efficacy of the proposed approach in enhancing the quality of reconstructed images compared to other competitive variational reconstruction methods. In conclusion, the simultaneous incorporation of sparsity priors of high-order TV and non-local similarity proves advantageous for structural detail recovery in sparse-view CT reconstruction.

Linear Beam-Down Solar Field Demonstrator: First Results and Validation

Linear beam-down solar fields consist of two stages of reflections that allow to concentrate solar irradiance at ground level. This approach seems promising for coupling with certain industries that require process heat, such as in mining and asphalt industries, in order to reduce their carbon emissions. In this work, the design and construction of a first of its kind linear beam-down Fresnel prototype is presented. First tests show that for the current solar field configuration, concentrations of up to 4.53 suns are achieved for a summer day at around 4 PM local time (UTC +2). Simulation projections show that this result could be enhanced to obtain up to 11.5 suns under the same solar conditions, by improving the mirror aiming system.

Multipole analysis of cluster weak lensing shear in The Three Hundred project

Weak gravitational lensing is an important tool to estimate the masses of galaxy clusters, as it allows us to directly access their projected surface mass density along the line of sight in a manner largely independent of their dynamical state. Moreover, we can extract information on the projected shape of the cluster mass distribution. In this work, we generate mock catalogs of lensed background galaxies to measure the individual lensing properties of galaxy clusters from the simulation project The Three Hundred. By repeating the analysis for different projections of the same cluster, we find that the use of shear multipoles provides constraints on the ellipticity of the cluster projected mass density but does not have a significant impact on the cluster mass reconstruction compared to the standard approach.

A coupling coordination development model of new energy electric vehicles and ecological environment

Analysing the degree of coupling and coordination between new energy electric vehicles and ecological environment in China is of great significance to optimize and enhance the development of new energy vehicles in China. This paper constructs the evaluation index system of China’s new energy development and ecological environment level respectively, and analyses the coupling and coordination level of the two based on the game theory combination empowerment method, the simulated annealing optimization projection tracing evaluation model and the coupling coordination degree model. The results show that the coupling degree of coordination gradually increases from 0.292 in 2010 to 0.828 in 2021, and the impact of the development of new energy electric vehicles on the ecological environment in China presents a positive and positive development year by year.

Impact of greenhouse warming on mesoscale eddy characteristics in high-resolution climate simulations

Mesoscale eddies are prevalent throughout the global ocean and have significant implications on the exchange of heat, salt, volume, and biogeochemical properties. These small-scale features can potentially influence regional and global climate systems. However, the effects of climate change on ocean eddies remain uncertain due to limited long-term observational data. To address this knowledge gap, our study focuses on examining the impact of greenhouse warming on surface mesoscale eddy characteristics, utilizing a high-resolution climate simulation project. Our model experiments provided valuable insights into the potential effects of greenhouse warming on mesoscale eddies, suggesting that mesoscale eddies will likely become more frequent under greenhouse warming conditions and exhibit larger amplitudes and radii, especially in regions characterized by strong ocean currents such as the Antarctic Circumpolar Current and western boundary currents. However, a distinctive pattern emerged in the Gulf Stream, with increases in eddy occurrence and radius and significant decreases in eddy amplitude. This phenomenon can be attributed to the relationship between eddy lifespans and their properties. Specifically, in the Kuroshio Current, the amplitude of eddies increased due to the increased occurrence of long-lived eddies. In contrast, in the Gulf Stream, the amplitude of eddies decreased significantly due to the decreased occurrence of long-lived eddies. This distinction arises from the fact that long-lived eddies can accumulate more energy than shorter-lived eddies throughout their lifetime. These findings provide valuable insights into the complex dynamics of mesoscale eddies in a warming world.

Interprofessional education collaborative: A pilot simulation project

BackgroundInterprofessional education (IPE) is fundamental to healthcare because good team functioning is associated with good patient outcomes, increased staff satisfaction, and high quality of patient care. This paper will discuss an IPE collaboration at a university in Southwest Georgia in partnership with the local health care facility with nursing students and a variety of allied health students. InnovationThe mission of the project was to facilitate interprofessional simulation opportunities and academic-practice partnerships among health care faculty, professionals, and students. The goals were to establish four interprofessional competency domains for collaborative practice: values/ethics, roles/responsibilities, interprofessional communication, and teamwork during an interdisciplinary simulation experience. ResultsAt the completion of the collaborative IPE, participants from the respective educational disciplines were able to appreciate the four interprofessional competency domains. More IPE simulations are recommended to enhance learners’ knowledge and skills. ConclusionThe collaboration among all health care students will lay the groundwork for more advanced learning activities and can offer immense opportunities for students to be “practice ready” graduates into the workforce which leads to improvements in patient outcomes.

A new rectangular dielectric resonator sensor for glucose measurement: Design, modeling, and experimental validation

SummaryThis study introduces a novel sensor for glucose measurement based on a rectangular dielectric resonator (RDR) excited by a rectangular slot fed by a 50‐Ω microstrip line. The RDR operates at 6 GHz and incorporates a cubic portion section for accommodating a finger or container containing the test sample. By utilizing the distinctive resonant frequencies associated with varying dielectric permittivity of different glucose concentrations, the proposed RDR functions as a reliable sensor. The sensor's performance is evaluated through a 3D electromagnetic model of the human thumb and the application of the Cole‐Cole method for modeling the blood layer. Experimental validation is conducted using three alternatives (water, glucose, and alcohol) and a range of glucose concentrations (70 to 2000 mg/dL) in simulation. During experimental verification, an invasive glucometer is employed as a reference for blood sugar levels. Results demonstrate that the proposed RDR sensor exhibits higher sensitivity (36.86 MHz/(mg/dL)) than other sensor counterparts. The experimental outcomes confirm the resonance frequency alignment between the manufactured sensor and the simulated projections. Considering its economic viability and applicability, this sensor represents a promising alternative biosensor for monitoring blood glucose levels.

Simulation-driven training of vision transformers enables metal artifact reduction of highly truncated CBCT scans.

Due to the high attenuation of metals, severe artifacts occur in cone beam computed tomography (CBCT). The metal segmentation in CBCT projections usually serves as a prerequisite for metal artifact reduction (MAR)algorithms. The occurrence of truncation caused by the limited detector size leads to the incomplete acquisition of metal masks from the threshold-based method in CBCT volume. Therefore, segmenting metal directly in CBCT projections is pursued in thiswork. Since the generation of high quality clinical training data is a constant challenge, this study proposes to generate simulated digital radiographs (dataI) based on real CT data combined with self-designed computer aided design (CAD) implants. In addition to the simulated projections generated from 3D volumes, 2D x-ray images combined with projections of implants serve as the complementary data set (dataII) to improve the network performance. In this work, SwinConvUNet consisting of shift window (Swin) vision transformers (ViTs) with patch merging as encoder is proposed for metalsegmentation. The model's performance is evaluated on accurately labeled test datasets obtained from cadaver scans as well as the unlabeled clinical projections. When trained on the dataI only, the convolutional neural network (CNN) encoder-based networks UNet and TransUNet achieve only limited performance on the cadaver test data, with an average dice score of 0.821 and 0.850. After using both dataII and dataI during training, the average dice scores for the two models increase to 0.906 and 0.919, respectively. By replacing the CNN encoder with Swin transformer, the proposed SwinConvUNet reaches an average dice score of 0.933 for cadaver projections when only trained on the dataI. Furthermore, SwinConvUNet has the largest average dice score of 0.953 for cadaver projections when trained on the combined dataset. Our experiments quantitatively demonstrate the effectiveness of the combination of the projections simulated under two pathways for network training. Besides, the proposed SwinConvUNet trained on the simulated projections performs state-of-the-art, robust metal segmentation as demonstrated on experiments on cadaver and clinical data sets. With the accurate segmentations from the proposed model, MAR can be conducted even for highly truncated CBCTscans.

Deep silicon photon-counting CT: A first simulation-based study for assessing perceptual benefits across diverse anatomies

ObjectivesTo assess perceptual benefits provided by the improved spatial resolution and noise performance of deep silicon photon-counting CT (Si-PCCT) over conventional energy-integrating CT (ECT) using polychromatic images for various clinical tasks and anatomical regions. Materials and MethodsAnthropomorphic, computational models were developed for lungs, liver, inner ear, and head-and-neck (H&N) anatomies. These regions included specific abnormalities such as lesions in the lungs and liver, and calcified plaques in the carotid arteries. The anatomical models were imaged using a scanner-specific CT simulation platform (DukeSim) modeling a Si-PCCT prototype and a conventional ECT system at matched dose levels. The simulated polychromatic projections were reconstructed with matched in-plane resolutions using manufacturer-specific software. The reconstructed pairs of images were scored by radiologists to gauge the task-specific perceptual benefits provided by Si-PCCT compared to ECT based on visualization of anatomical and image quality features. The scores were standardized as z-scores for minimizing inter-observer variability and compared between the systems for evidence of statistically significant improvement (one-sided Wilcoxon rank-sum test with a significance level of 0.05) in perceptual performance for Si-PCCT. ResultsSi-PCCT offered favorable image quality and improved visualization capabilities, leading to mean improvements in task-specific perceptual performance over ECT for most tasks. The improvements for Si-PCCT were statistically significant for the visualization of lung lesion (0.08 ± 0.89 vs. 0.90 ± 0.48), liver lesion (-0.64 ± 0.37 vs. 0.95 ± 0.55), and soft tissue structures (-0.47 ± 0.90 vs. 0.33 ± 1.24) and cochlea (-0.47 ± 0.80 vs. 0.38 ± 0.62) in inner ear. ConclusionsSi-PCCT exhibited mean improvements in task-specific perceptual performance over ECT for most clinical tasks considered in this study, with statistically significant improvement for 6/20 tasks. The perceptual performance of Si-PCCT is expected to improve further with availability of spectral information and reconstruction kernels optimized for high resolution provided by smaller pixel size of Si-PCCT. The outcomes of this study indicate the positive potential of Si-PCCT for benefiting routine clinical practice through improved image quality and visualization capabilities.