Development Of Simulation Tool Research Articles

A Novel Temperature-Independent Model for Estimating the Cooling Energy in Residential Homes for Pre-Cooling and Solar Pre-Cooling

Australia’s electricity networks are experiencing low demand during the day due to excessive residential solar export and high demand during the evening on days of extreme temperature due to high air conditioning use. Pre-cooling and solar pre-cooling are demand-side management strategies with the potential to address both these issues. However, there remains a lack of comprehensive studies into the potential of pre-cooling and solar pre-cooling due to a lack of data. In Australia, however, extensive datasets of household energy measurements, including consumption and generation from rooftop solar, obtained through retailer-owned smart meters and household-owned third-party monitoring devices, are now becoming available. However, models presented in the literature which could be used to simulate the cooling energy in residential homes are temperature-based, requiring indoor temperature as an input. Temperature-based models are, therefore, precluded from being able to use these newly available and extensive energy-based datasets, and there is a need for the development of new energy-based simulation tools. To address this gap, a novel data-driven model to estimate the cooling energy in residential homes is proposed. The model is temperature-independent, requiring only energy-based datasets for input. The proposed model was derived by an analysis comparing the internal free-running and air conditioned temperature data and the air conditioning data for template residential homes generated by AccuRate, a building energy simulation tool. The model is comprised of four linear equations, where their respective slope intercepts represent a thermal efficiency metric of a thermal zone in the template residential home. The model can be used to estimate the difference between the internal free-running, and air conditioned temperature, which is equivalent to the cooling energy in the thermal zone. Error testing of the model compared the difference between the estimated and AccuRate air conditioned temperature and gave average CV-RMSE and MAE values of 22% and 0.3 °C, respectively. The significance of the model is that the slope intercepts for a template home can be applied to an actual residential home with equivalent thermal efficiency, and a pre-cooling or solar pre-cooling analysis is undertaken using the model in combination with the home’s energy-based dataset. The model is, therefore, able to utilise the newly available extensive energy-based datasets for comprehensive studies on pre-cooling and solar pre-cooling of residential homes.

Advanced finite element model for predicting surface integrity in high-speed turning of AA7075-T6 under dry and cryogenic conditions

The overall quality of a component and its mechanical performance and reliability during all its life cycle depend on several characteristics. The choice of the material plays an important role in satisfying the requirements and usually it makes the difference between failed and not failed products; however, another significant impact in the material performances is characterised by the manufacturing process. Nowadays, the numerical simulation represents an important tool to quickly predict several scenarios depending on process parameters’ changes, leading to a more flexible manufacturing process and time–cost saving due to the reduced experimental tests. This work presents an innovative finite element model (FEM) of high-speed turning of one of the most used aluminium alloys in aerospace field, namely the AA7075-T6. The developed simulation tool allowed to better investigate the metallurgical phenomena triggered by the varying process parameters tested and the cooling conditions used during the machining tests. A physics-based model to simulate the material behaviour has been developed and implemented via subroutine within the FEM software. The predictive capability of the model has been validated through experimental and numerical comparison of cutting forces, maximum temperature and grain size changes. The developed 3D FE model is capable of including the effects of different cooling conditions during machining of the aluminium alloy AA7075-T6 on the surface integrity (e.g. the microstructure and the dislocation density variation), whilst evaluating further important manufacturing process variables as cutting forces and maximum temperature.

HSD34 The Development and Validation of a Novel Discrete Simulation Tool for Modeling the Operational Efficiency of Inpatient Electrophysiology Services

HSD34 The Development and Validation of a Novel Discrete Simulation Tool for Modeling the Operational Efficiency of Inpatient Electrophysiology Services

Development of Clinical Trial Simulation Tools for Alzheimer’s Disease through the Critical Path for Alzheimer’s Disease (CPAD) Consortium

AbstractBackgroundCritical Path Institute (C‐Path) coordinates the Critical Path for Alzheimer’s Disease (CPAD) Consortium. To accelerate DRUG DEVELOPMENT for Alzheimer’s Disease (AD), CPAD developed two regulatory‐endorsed clinical trial simulation (CTS) that sponsors can use to help optimize clinical trial design in 1) the pre‐dementia stages of AD, using CDR‐SB as the primary endpoint, and 2) mild‐to‐moderate AD, using ADAS‐cog as the primary cognitive endpoint. Recently, CPAD members have shared data from several contemporary Phase III clinical trials, offering an opportunity to enrich and expand these model‐based tools with additional fluid and imaging biomarker information, data from predementia subjects and treatment arms.MethodBy integrating patient‐level data from high quality Alzheimer’s disease (AD) clinical trials, models will be developed for multiple endpoints, and including demographics, time from and to diagnosis, genetic status (APOE4), and will be assessed using non‐linear mixed effects methods. Monte Carlo simulations will be performed to compare the statistical power by sample size in trials with and without enrichment using relevant covariates.ResultAs of January 2022, CPAD’s clinical trial repository contains 55 studies with 36,344 individual anonymized patient records. Analysis subsets generated from 6 key datasets, rich in fluid and imaging biomarkers, were used to develop of a preliminary set of disease progression models that characterize the time course of clinically relevant measures (ADAS‐Cog, CDR‐SB, other clinical assessment scales and biomarkers). A two‐level regression model was applied to predict baseline CDR‐SB using baseline covariates (demography, ApoE4 status, fluid and imaging biomarkers) and identify significant variables. Base models using parametric mixed‐effects approaches were developed with selection based on goodness‐of‐fit plots.ConclusionThe disease progression models will serve as the basis for clinical trial simulation tools to facilitate informed decision making in the DRUG DEVELOPMENT process and optimize patient and endpoint selection, as well as design of efficacy studies. CPAD will advance the tools through the formal FDA Fit for Purpose pathway, to achieve regulatory endorsement and provide confidence to sponsors for the adoption of the tools.

Laser speckle simulation tool based on stochastic differential equations for bio imaging applications.

Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood flow (a few cm) as well. A means of simulating laser speckles is often necessary for the analysis and development of these imaging modalities, as evident from many such attempts towards developing simulation tools in the past. Such methods often employ Fourier transforms or statistical tools to simulate speckles with desired statistical properties. We present the first method to use a stochastic differential equation to generate laser speckles with a pre-determined probability density function and a temporal auto-correlation. The method allows the choice of apriori gamma distribution along with simple exponential or more complex temporal auto-correlation statistics for simulated speckles, making it suitable for different blood flow profiles. In contrast to the existing methods that often generate speckles associated with superficial flow, we simulate both superficial and diffuse speckles leading to applications in deep tissue blood flow imaging. In addition, we have also incorporated appropriate models for noise associated with the detectors to simulate realistic speckles. We have validated our model by comparing the simulated speckles with those obtained from in-vivo studies in mice and healthy human subject.

Development of a Model Rocket Trajectory Simulation Tool with Python

Within any space mission, the design of the trajectory that the spacecraft will travel across is one of the essential and most important steps. For the launch of smaller rockets, this is also a key analysis to be done during the development of the project, ensuring that the rocket achieves its flight objectives and enabling the definition of a safety radius based on its landing site. Therefore, the present work proposes the development of a tool to simulate the trajectory of small rockets that is satisfactory for use in academic projects, acting as a free alternative to similar software available on the market. For this task, the Python programming language is used, due to its open-source characteristic and shorter execution times compared to similar languages during the execution of numerical computation methods, which are necessary for modeling the rocket's flight dynamics. The results found with the use of the tool for simulating the trajectory of a model rocket are sufficient for the purpose of this work, reaching similar findings to those of simulations carried out in OpenRocket (a JAVA rocket trajectory simulation software, widely used in academic space). Moreover, a Monte Carlo simulation is performed, in which an impact point dispersion radius is estimated.

189 IMPROVING DEMENTIA CARE THROUGH SELF-EXPERIENCE; CO-DESIGNING A SIMULATION-BASED DEMENTIA EDUCATION TOOLKIT

Abstract Background Although specialised dementia education programmes have begun to appear in recent years, they lack consistency. Knowledge gaps persist, which results in a professional workforce who can struggle to anticipate the care needs of people with dementia. Self-experience or simulation practices (e.g., roleplays, virtual reality, sensory tools) are established teaching methods that can provide learning opportunities to experience aspects of illness. These innovative learning approaches can positively impact empathy, understanding, and quality of care; however, they are rarely implemented in specialised care for people with dementia. The Improving demeNtia care Through Self-Experience (INTENSE) project has co-designed a dementia simulation toolkit to educate, equip, and train professionals to better support people with dementia. Methods As part of the Erasmus+ INTenSE project, a series of three participatory, online workshops were conducted with people with dementia, informal caregivers, and dementia-care professionals in Ireland, Italy, Germany, and the Netherlands. The first explored the co-design of training scenarios using simulation tools to demonstrate the lived experience of dementia. The second involved the co-design of an online training platform. The third examined the sustainable implementation of INTenSE into practice. All workshops were inductively coded and analysed thematically. Results Recommended training scenarios demonstrate daily activities and environments that impact people with dementia using a combination of existing and newly developed simulation tools. Four themes arose from workshop discussions: 1) representation of dementia, 2) daily challenges that impact people with dementia, 3) applying a person-centred approach, and 4) implementing self-experience training. Together these were used to develop facilitation guides to support the implementation of the INTenSE simulation toolkit into practice. Conclusion These findings demonstrate the potential of simulating self-experience across a range of everyday scenarios as a means to increase professionals' empathy and understanding of the lived experience of dementia. Recommendations have been developed that support the use of self-experience tools in practice.

Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems

In this work, we report on modeling results obtained with our recently developed simulation tool enabling nanoscopic description of electronic processes in X-ray irradiated ferromagnetic materials. With this tool, we have studied the response of Co/Pt multilayer system irradiated by an ultrafast extreme ultraviolet pulse at the M-edge of Co (photon energy ~60 eV). It was previously investigated experimentally at the FERMI free-electron-laser facility, using the magnetic small-angle X-ray scattering technique. Our simulations show that the magnetic scattering signal from cobalt decreases on femtosecond timescales due to electronic excitation, relaxation, and transport processes both in the cobalt and in the platinum layers, following the trend observed in the experimental data. The confirmation of the predominant role of electronic processes for X-ray induced demagnetization in the regime below the structural damage threshold is a step toward quantitative control and manipulation of X-ray induced magnetic processes on femtosecond timescales.

Simulation of impact force generated by an ISO tapping machine on a wooden slab using explicit dynamics analysis

Application of simulation tools to compute impact sound insulation properties of wooden floors has raised interests in recent decades. To achieve accurate results from the prediction models, information from force excitation generated by impact sound sources is required. The purpose of our study was to present a validated procedure to determine the non-linear impact force excitation generated by an ISO tapping machine. The method comprised use of finite element method (FEM) and explicit time integration to compute impact force pulse generated by a hammer of the tapping machine. With a post-processing procedure, the force pulses can be converted to present point forces describing the continuous operation of the tapping machine on the floor. To demonstrate the applicability of the method, the finite element model was applied to imitate an experimental situation on a cross-laminated timber (CLT) slab. The model validation showed that the computational model closely predicts the force pulse generated on the CLT slab. Findings from a sensitivity analysis revealed that local properties of the slab were the most important to the simulated impact force pulse. The findings of the analysis are helpful for those developing simulation tools to compute the impact force generated by the tapping machine on wooden floors.

Fission Battery transportation and siting aspects

Fission Batteries (FBs) are envisioned to be highly mobile, autonomously operating, and economically competitive small nuclear power reactor systems useable for generating electric power or heat. Such novel systems will face unique challenges pertaining to siting and transportation. This paper presents the findings and recommendations of the 2021 Idaho National Laboratory FB Initiative workshop on the transportation and siting of FBs. Regulatory and technical subject matter experts on the transportation and storage of radioactive materials, licensing of nuclear power plants, innovative sensing technologies, etc., participated in this workshop and shared their professional experiences and perspectives. Based on these conversations, the paper describes the lessons learned from nuclear reactor siting and licensing, as well as from the siting and transportation of radioactive materials such as fresh or spent nuclear fuel. It then explores the applicability of these lessons and practices to FB siting and transportation. In addition, associated regulatory and technological challenges are identified, such as a changing FB source term, criticality safety aspects, neutron activation and embrittlement of structural components, site development, transportation uncertainties, the current regulatory framework, modeling and simulation uncertainties, and limited inspections. Additionally, research and development activities are suggested to address these gaps and challenges, including the development of modeling and simulation tools for FB design, strategies for rapid FB transportation, innovative FB shell materials, procedures for onsite handling of FBs, transportation-accident-proof criticality control mechanisms, self-monitoring and self-testing capabilities, regulatory requirements, and probabilistic risk assessment tools. Carrying out these research initiatives is expected to help accelerate the evolution of FBs and facilitate their design, licensing, and deployment.

Agent Simulation Model of COVID-19 Epidemic Agent-Based on GIS: A Case Study of Huangpu District, Shanghai.

Since the COVID-19 outbreak was detected and reported at the end of 2019, the pandemic continues worldwide, with public health authorities and the general public in each country struggling to balance safety and normal travel activities. However, the complex public health environment and the complexity of human behaviors, as well as the constant mutation of the COVID-19 virus, requires the development of theoretical and simulation tools to accurately model all segments of society. In this paper, an agent-based model is proposed, the model constructs the real geographical environment of Shanghai Huangpu District based on the building statistics data of Shanghai Huangpu District, and the real population data of Shanghai Huangpu District based on the data of China’s seventh Population census in 2020. After incorporating the detailed elements of COVID-19 transmission and the real data of WHO, the model forms various impact parameters. Finally, the model was validated according to the COVID-19 data reported by the official, and the model is applied to a hypothetical scenario. Shanghai is one of the places hardest hit by the current outbreak, Huangpu District is the “heart, window and name card” of Shanghai, and its importance to Shanghai is self-evident. so we used one-to-one population modeling to simulate the spread of COVID-19 in Huangpu District of Shanghai, In addition to the conventional functions of crowd movement, detection and treatment, the model also takes into account the burden of nucleic acid detection on the model caused by diseases similar to COVID-19, such as seasonal cold. The model validation results show that we have constructed a COVID-19 epidemic agent risk assessment system suitable for the individual epidemiological characteristics of COVID-19 in China, which can adjust and reflect on the existing COVID-19 epidemic intervention strategies and individual health behaviors. To provide scientific theoretical basis and information decision-making tools for effective prevention and control of COVID-19 and public health intervention in China.

Crystal-based pair production for a lepton collider positron source

An intense positron sources is a demanding element in the design of future lepton colliders. A crystal-based hybrid positron source could be an alternative to a more conventional scheme based on the electron conversion into positron in a thick amorphous target. The conceptual idea of the hybrid source is to have two separate objects, a photon radiator and a photon-to-positron converter target. In such a scheme an electron beam crosses a thin axially oriented crystal with the emission of a channeling radiation, characterized by a considerably larger amount of photons if compared to Bremsstrahlung. The net result is an increase in the number of produced positrons at the converter target. In this paper we present the results of a beam test conducted at the DESY TB 21 with 5.6 GeV electron beam and a crystalline tungsten radiator. Experimental data clearly highlight an increased production of photons and they are critically compared with the outcomes of novel method to simulate the number of radiated photons, showing a very good agreement. Strong of this, the developed simulation tool has been exploited to design a simple scheme for a positron source based on oriented crystal, demonstrating the advantages in terms of reduction of both deposited energy and the peak energy deposition density if compared to conventional sources. The presented work opens the way for a realistic and detailed design of a hybrid crystal-based positron source for future lepton colliders.

Construction and Verification of a Model for Estimating Electricity Consumption of Residential Buildings in a Region for the Development of an Area Energy Demand Simulation Tool

Construction and Verification of a Model for Estimating Electricity Consumption of Residential Buildings in a Region for the Development of an Area Energy Demand Simulation Tool

Optimal design of a 5th generation district heating and cooling network based on seawater heat pumps

This work presents the design and the thermo-economic optimization of a novel layout of a 5th generation district heating and cooling network, for a residential district located in the Pantelleria island (South of Italy). The research focuses on a novel arrangement based on two bidirectional low-temperature neutral rings. For both rings, the fluid temperature is controlled by means of two groups of heat pumps cooled by seawater. The investigated layout also includes wind turbines and photovoltaic panels for power production. This layout will be used as a driver to promote the transition from the present centralized energy paradigm to a novel one, based on small-scale distributed generation integrated with renewables. The paper aims at evaluating the energy, economic and environmental savings achieved by this novel layout. A thermo-economic optimization is also implemented in order to determine the set of design/operating variables, maximizing system economic profitability. To this scope, a detailed approach is implemented, developing a dynamic simulation model of the system in TRNSYS 17. The developed simulation tool is able to mimic the real time operation of the system, for whatever weather condition, boundary and/or design variable. The results of the simulations show that the proposed layout achieves significantly positive results, with a primary energy saving and avoided greenhouse gases emissions equal to 133% and 134%, respectively. The economic profitability of the system is limited with the payback period close to 15 years, due to the high capital cost of the plant. The renewable electric production of the plant meets 57% of the district demand, although only 37% of this amount is self-consumed by the district. The study also includes a sensitivity analysis suggesting to limit the capacities of solar and wind fields to reduce the electricity in excess sold to the grid.

Emergency Response System Combining the Internal and External Domains (ERSCIED)

Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR) operations. The previous studies aimed to develop a dynamic agent-based simulation model in post-earthquake emergency response operations combining rescuers and victims using geospatial information systems and multi-agent systems (GISs and MASs, respectively). We use multi-agent system engineering (MaSE) to construct this model and cluster points are proposed to assemble rescuers and victims. We also proposed an approach for dynamic task allocation and for establishing collaboration among agents based on contract net protocol (CNP) and the [Formula: see text]-means clustering method. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and expert evaluation is used to sort the priorities of cluster points. The experimental background is set in the central area of Chengdu, Sichuan Province, China. 200 victims with different demands and 30 rescuers with the same rescue capability are randomly distributed in this area. We use different victim speeds to simulate different degrees of seismic damage. Compared with normal search and rescue, the ERSCIED can make some use of the capabilities of the victims for the improvement of emergency effectiveness when the victims and rescuers have a similar speed (1:1) or the victims are not much slower than the rescuers (1:2). When the victims are much slower than the rescuers (1:10), the rescuers have to wait for a long time at the cluster points and it will lead to a waste of resources. The parameters of rescuers and victims can be changed to meet different emergencies and the ERSCIED can provide effective auxiliary decision-making information for decision-makers.

Machine-learning convex and texture-dependent macroscopic yield from crystal plasticity simulations

The influence of the microstructure of a polycrystalline material on its macroscopic deformation response is still one of the major problems in materials engineering. For materials characterized by elastic-plastic deformation responses, predictive computational models to characterize crystal-plasticity (CP) have been developed. However, due to their large demand of computational resources, CP simulations cannot be straightforwardly implemented in hierarchical computational models such as FE2. This bottleneck intensifies the need for the development of macroscopic simulation tools that can be directly informed by microstructural quantities. Using a 3D finite element solver for CP, we generate a macroscopic yield function database based on general loading conditions and crystallographic texture. Leveraging the advancement in statistical modeling we describe and apply a machine learning framework for predicting plane stress macroscopic yield as a function of crystallographic texture. The convexity of the data-driven yield function is guaranteed by using partially input convex neural networks as the predictive tool. Furthermore, in order to allow for the predicted yield function to be directly incorporated in time-integration schemes, as needed for the finite element method, the yield surfaces are interpreted as the boundaries of signed distance function level sets. Results generated for an example cube texture are discussed.

A pressure‐based method for weakly compressible two‐phase flows under a Baer–Nunziato type model with generic equations of state and pressure and velocity disequilibrium

AbstractWithin the framework of diffuse interface methods, we derive a pressure‐based Baer–Nunziato type model well‐suited to weakly compressible multiphase flows. The model can easily deal with different equation of states and it includes relaxation terms characterized by user‐defined finite parameters, which drive the pressure and velocity of each phase toward the equilibrium. There is no clear notion of speed of sound, and thus, most of the classical low Mach approximation cannot easily be cast in this context. The proposed solution strategy consists of two operators: a semi‐implicit finite‐volume solver for the hyperbolic part and an ODE integrator for the relaxation processes. Being the acoustic terms in the hyperbolic part integrated implicitly, the stability condition on the time step is lessened. The discretization of nonconservative terms involving the gradient of the volume fraction fulfills by construction the nondisturbance condition on pressure and velocity to avoid oscillations across the multimaterial interfaces. The developed simulation tool is validated through one‐dimensional simulations of shock‐tube and Riemann‐problems, involving water‐aluminum and water‐air mixtures, vapor‐liquid mixture of water and of carbon dioxide, and almost pure flows. The numerical results match analytical and reference ones, except some expected discrepancies across shocks, which however remain acceptable (errors within some percentage points). All tests were performed with acoustic CFL numbers greater than one, and no stability issues arose, even for CFL greater than 10. The effects of different values of relaxation parameters and of different amount equations of state—stiffened gas and Peng–Robinson—were investigated.

Validation of tsunami numerical simulation models for an idealized coastal industrial site

ABSTRACT Numerous tsunami numerical models have been proposed, but their prediction accuracies have not been directly compared. For quantifying the modeling uncertainties, the authors statistically analyzed the prediction results submitted by participants in the tsunami blind contest held at the 17th World Conference on Earthquake Engineering. The reproducibility of offshore water level generated due to the tsunami with soliton fission significantly decreased when the nonlinear shallow water equation models (NSWE) was used compared to three-dimensional (3D) models. The inundation depth was reproduced well in 3D models. However, the reproducibility of wave forces acting on the structure and velocities over land was lower in 3D models than that in NSWE models. For cases where the impulsive tsunami wave pressure generated could not be calculated based on the hydrostatic assumption, the prediction accuracy of the NSWE models was higher than that of the 3D models. The prediction accuracies of both models were not improved at small grid-cell sizes. The NSWE model cannot simulate the short-wave component and vertical pressure distribution. Therefore, further developments in 3D models and smoothed particle hydrodynamics methods (SPH) are needed. The presented results contribute to the future development of tsunami numerical simulation tools.

Multiphysics analysis of RANS-based turbulent transport of solid fission products in the Molten Salt Fast Reactor

The analysis of innovative reactor concepts such as the Molten Salt Fast Reactor (MSFR) requires the development of new modeling and simulation tools. In the case of the MSFR, the strong intrinsic coupling between thermal–hydraulics, neutronics and fuel chemistry has lead to the adoption of the multiphysics approach as a state-of-the-art paradigm. One of the peculiar aspects of liquid-fuel reactors such as the MSFR is the mobility of fission products (FPs) in the reactor circuit. Some FP species appear in form of solid precipitates carried by the fuel flow and can deposit on reactor boundaries (e.g., heat exchangers), potentially representing design issues related to the degradation of heat exchange performance or radioactive hotspots. Other precipitates might be present in the primary system as well, e.g. due to oxidation of fissile species which might lead to local criticality issues. The integration of transport models for solid particles in multiphysics codes is therefore relevant for the prediction of deposited fractions. To this aim, a previously developed Eulerian single-phase transport model is employed to analyze the distribution of solid FPs in two simplified MSFR-related geometries. The effect of physical parameters and of distributed particle sources on the numerical requirements needed to resolve particle concentration gradients at reactor boundaries in the considered geometries is investigated with the aid of analytical results. Analytical estimates of concentration gradients, even though not in full agreement with simulations, prove useful to drive the choice of adequate mesh refinements. Furthermore, the influence of different RANS turbulence modeling approaches on the prediction of particle distributions and deposition is tested. Results show a limited influence of the choice of turbulence models and parameters on the deposited fraction and on concentration gradients. As a result, it is found that deposition rates are scarcely affected by the choice of turbulent Schmidt number, with lower diffusivities being compensated by larger gradients. Large deposited fractions are indeed predicted, suggesting the efficiency of FPs transport mechanisms in the reactor and the need for the integration of adequate FPs transport models within state-of-the-art MSFR codes.

Advancing simulation tools specific to floating solar photovoltaic systems – Comparative analysis of field-measured and simulated energy performance

The land-use intensity and performance-related issues in the solar energy sector have led to the development of floating photovoltaic (FPV) systems that allow solar photovoltaic (PV) installation on water bodies. The FPV systems present two-fold benefits in terms of mitigation of land-use conflicts and improved energy performances. While such experimental studies exist in the literature, the critical apprehensions related to performance feasibility assessments during the project planning are still unclear due to the lack of simulation tools specific to the FPV. Also, given the high uncertainty in solar PV performance, which varies from location to location, the existing experimental studies may not help in benchmarking and revealing the need for simulations specific to FPV. In reality, most installers/researchers are still using simulation tools that apply to conventional PV installations, and that do not account for the PV-water interaction and cooling effect caused. Until now, without realising this, the service providers are providing inaccurate performance feasibility reports to clients who wish to deploy FPV. Hence, this study investigates whether the existing simulation tools can be applied for FPV planning by taking a 2 MWp FPV power plant installed on the urban water reservoir in Southern India as a case study. First, the field measured data of the 2 MWp FPV plant is monitored. Second, the same is simulated in three different software tools: PVsyst, System Advisory Model (SAM) by National Renewable Energy Laboratory (NREL), and Helioscope. Third, error metrics-based methodology is applied to understand the deviation in energy output, capacity utilization factor (CUF), and performance ratio (PR). The results advocate that deviation in energy from the measured to simulated varies significantly from 18.43 to 38.55%, suggesting that none of the considered simulation tools suitable for FPV project planning. Similarly, other performance indicators are analysed, followed by a discussion and data-driven recommendations leading to the conceptual simulation tool development for FPV.