Dummy Model Research Articles

Metallicious: Automated Force-Field Parameterization of Covalently Bound Metals for Supramolecular Structures.

Metal ions play a central, functional, and structural role in many molecular structures, from small catalysts to metal-organic frameworks (MOFs) and proteins. Computational studies of these systems typically employ classical or quantum mechanical approaches or a combination of both. Among classical models, only the covalent metal model reproduces both geometries and charge transfer effects but requires time-consuming parameterization, especially for supramolecular systems containing repetitive units. To streamline this process, we introduce metallicious, a Python tool designed for efficient force-field parameterization of supramolecular structures. Metallicious has been tested on diverse systems including supramolecular cages, knots, and MOFs. Our benchmarks demonstrate that parameters accurately reproduce the reference properties obtained from quantum calculations and crystal structures. Molecular dynamics simulations of the generated structures consistently yield stable simulations in explicit solvent, in contrast to similar simulations performed with nonbonded and cationic dummy models. Overall, metallicious facilitates the atomistic modeling of supramolecular systems, key for understanding their dynamic properties and host-guest interactions. The tool is freely available on GitHub (https://github.com/duartegroup/metallicious).

Impact responses and injury analyses of a three-year-old occupant seating in forward and rearward facing CRSs using different computational models

To investigate the reliability and necessity of utilising a human biomechanical model in automotive safety, the frontal collision simulation test was conducted employing the TUST IBMs 3YO model and the Q3 dummy model. The kinematic and biomechanical injury parameters of the occupants were comparatively analysed. The results indicate consistent trends in acceleration changes between the two computational models. Variations in neck structure resulted in a 25% to 28% difference in the peak values of neck injury parameters. Differences in spine structure and materials made the spine angle change trends of the Q3 model more sensitive to the type of child restraint system (CRS). The human biomechanical model allows for the evaluation of occupant injury risk from multiple perspectives. Therefore, employing an advanced computational model of the human body with higher biofidelity provides a more reliable and effective method for investigating injury mechanisms and developing protective countermeasures for child occupants.

Identifying the influence of airbag structure on driver injury during a crash using a dummy model

This study undertakes the analysis of collision scenario using a car model with a dummy and airbags, in the event of a direct collision with a hard wall, one of the necessary studies of passive safety. To describe in detail, the input conditions, a simulation problem of the driver's seat displacements was performed and this displacements data was exported as boundary conditions for the collision simulation. The results simulation crash show that the calculated energy values and simulation results are approximately the same (7.381E+07 and 7.367E+07), energy is converted from kinetic energy into internal energy of the elements. The airbag deployment simulation results are similar to NHTSA's previous research, both in terms of graph shape and maximum value. The impact of the collision incident on the driver is not excessively large, as evidenced by surveys on head (HIC 300), thigh (F 2.8 kN), and neck (F3,098 kN; T 190 Nm) injuries. However, the study proceeds to further analyze and assess the airbag's structure, examining its influence on these metrics, concluding that changes in the exhaust valve size (increase from 1000 mm2 to 2000 mm2) lead to a reduction in the evaluated parameters. These results suggest changes to the airbag structure to enhance driver safety, as well as a simpler simulation model to save analysis time

Justification of necessity to develop the procedure for creation of finite-element models of dummies for vehicle virtual testing in terms of frontal and side impacts

Justification of necessity to develop the procedure for creation of finite-element models of dummies for vehicle virtual testing in terms of frontal and side impacts

The neck structure design of vehicle crash finite element dummy model

Anthropomorphic Test Devices (ATDs) with high biofidelity and compatibility play a crucial role in vehicle safety. This study focuses on enhancing the neck of Hybrid III finite element model by optimising its design and material. The improved Hybrid III model (IH3) is validated through neck calibration tests. Comparing to experimental results,IH3 has a peak torque error of only 1.00% and 5.11%and a 60.04% improvement in calculation efficiency. Then MLH3 with low stiffness and equivalent muscles and ligaments is designed and tested. The results of MLH3 show higher biofidelity than l than Hybrid III. Finally, both IH3 and MLH3 have been tested in a 100% frontal rigid barrier test, with IH3 showing significant accuracy and computational efficiency, indicating that it could replace the current Hybrid III neck for simulation analysis. MLH3 has potential engineering application value in the future, as it improves upon the limitations of the Hybrid III neck’s biofidelity and more closely resembles the real human neck.

The effectiveness of Q6 and PIPER 6-year-old models on quantification of the change of child sitting posture with AEB and its impact on child’s injures in frontal crash

Objective Automatic Emergency Braking (AEB) has a direct impact on the effectiveness of the restraint systems in providing protection toward child occupants. The objective is to evaluate the effectiveness of Q6 and PIPER 6-year-old models in predicting the kinematic responses of child models, and further to quantify and analyze the child injuries during a frontal crash with and without AEB. Methods The finite element model of a booster seat has been validated through a full vehicle test. Based on the validated finite element model, two sled test finite element models for the rear seat booster seat with Q6 and PIPER 6-year-old models were constructed. AEB condition was imposed on above the two models and the kinematic responses of sitting posture including head, neck and chest have been compared in detail. The peak head displacement and neck curvature of Q6 dummy and PIPER 6-year-old models have been compared with the test data from child volunteers. Based on the child model with better predictive capability for kinematic response under AEB, child injuries were evaluated and analyzed for the 50 km/h frontal crash test with and without AEB. Last, this study discussed the effects of internal neck and chest structure difference between Q6 and PIPER 6-year-old models on child kinematic response and the injury risks. Results Under AEB condition, PIPER 6-year-old model has higher head displacement and lower trunk displacement than Q6 dummy model, and the peak head displacement and neck curvature of PIPER 6-year-old model are similar to the test data of child volunteers. During the 50 km/h frontal crash simulation with pre-crash AEB, the HIC15, Head acceleration 3 ms, Nij decrease 43.7%, 19.6% and 28.8%, respectively and the chest deflection increases 15.5% compared to the simulation without AEB. Conclusions This study shows that PIPER 6-year-old model is more suitable for the quantification of sitting posture change under AEB due to its higher biofidelity. The pre-crash AEB can substantially reduce the head, neck injuries. But it also increases the chest injury due to the chest pre-compression. Future efforts are recommended to lower the child chest injury by integrating AEB with active pre-tensioning seatbelts.

Investigation on vehicle occupant dummy applicability for under-foot impact loading conditions

PurposeUnder-foot impact loadings can cause serious lower limb injuries in many activities, such as automobile collisions and underbody explosions to military vehicles. The present study aims to compare the biomechanical responses of the mainstream vehicle occupant dummies with the human body lower limb model and analyze their robustness and applicability for assessing lower limb injury risk in under-foot impact loading environments. MethodsThe Hybrid III model, the test device for human occupant restraint (THOR) model, and a hybrid human body model with the human active lower limb model were adopted for under-foot impact analysis regarding different impact velocities and initial lower limb postures. ResultsThe results show that the 2 dummy models have larger peak tibial axial force and higher sensitivity to the impact velocities and initial postures than the human lower limb model. In particular, the Hybrid III dummy model presented extremely larger peak tibial axial forces than the human lower limb model. In the case of minimal difference in tibial axial force, Hybrid III's tibial axial force (7.5 KN) is still 312.5% that of human active lower limb's (2.4 KN). Even with closer peak tibial axial force values, the biomechanical response curve shapes of the THOR model show significant differences from the human lower limb model. ConclusionBased on the present results, the Hybrid III dummy cannot be used to evaluate the lower limb injury risk in under-foot loading environments. In contrast, potential improvement in ankle biofidelity and related soft tissues of the THOR dummy can be implemented in the future for better applicability.

A reproducible ensemble machine learning approach to forecast dengue outbreaks

Dengue fever, a prevalent and rapidly spreading arboviral disease, poses substantial public health and economic challenges in tropical and sub-tropical regions worldwide. Predicting infectious disease outbreaks on a countrywide scale is complex due to spatiotemporal variations in dengue incidence across administrative areas. To address this, we propose a machine learning ensemble model for forecasting the dengue incidence rate (DIR) in Brazil, with a focus on the population under 19 years old. The model integrates spatial and temporal information, providing one-month-ahead DIR estimates at the state level. Comparative analyses with a dummy model and ablation studies demonstrate the ensemble model’s qualitative and quantitative efficacy across the 27 Brazilian Federal Units. Furthermore, we showcase the transferability of this approach to Peru, another Latin American country with differing epidemiological characteristics. This timely forecast system can aid local governments in implementing targeted control measures. The study advances climate services for health by identifying factors triggering dengue outbreaks in Brazil and Peru, emphasizing collaborative efforts with intergovernmental organizations and public health institutions. The innovation lies not only in the algorithms themselves but in their application to a domain marked by data scarcity and operational scalability challenges. We bridge the gap by integrating well-curated ground data with advanced analytical methods, addressing a significant deficiency in current practices. The successful transfer of the model to Peru and its consistent performance during the 2019 outbreak in Brazil showcase its scalability and practical application. While acknowledging limitations in handling extreme values, especially in regions with low DIR, our approach excels where accurate predictions are critical. The study not only contributes to advancing DIR forecasting but also represents a paradigm shift in integrating advanced analytics into public health operational frameworks. This work, driven by a collaborative spirit involving intergovernmental organizations and public health institutions, sets a precedent for interdisciplinary collaboration in addressing global health challenges. It not only enhances our understanding of factors triggering dengue outbreaks but also serves as a template for the effective implementation of advanced analytical methods in public health.

Using millimeter-wave radar to evaluate the performance of dummy models for advanced driving assistance systems test

With the rapid development of intelligent and connected vehicles, the experimental road test for the advanced driving assistance system (ADAS) is dramatically increasing around the world. Considering its high cost and hazardous situations, simulation test based on a dummy model is becoming a promising way for ADAS road test practice to reduce the experiment expanses. This study proposed a methodology for the evaluation of the performance of human and dummies with distinct designed materials based on the data extracted from the Doppler effect of millimeter-wave radar. Echo data of 8 different angles from 0 to 360 degrees, with the an interval of 45 degrees, at the same distance between the test object and the signal source is collected. Meanwhile, the echo energy is collected for correlation modeling and analysis among groups. By evaluating the performance of humans and dummies via statistical analysis, a close correlation was found which results verified the substitutability of the dummy for the ADAS experiment test. The correlation coefficient between human and dummies ranges from 0.75 to 0.93. The support vector machine (SVM) model was developed and fitted to predict the echo energy in diverse environments. The mean average error (MAE) is 5.42–11.42 in the training and testing datasets while root mean square error (RMSE) is 0.43–0.90. The methods developed in the study can simulate the real ADAS road test environment and support future experimental research.

Optimization of Occupant Restraint System Using Machine Learning for THOR-M50 and Euro NCAP

In this study, we propose an optimization method for occupant protection systems using a machine learning technique. First, a crash simulation model was developed for a Euro NCAP MPDB frontal crash test condition. Second, a series of parametric simulations were performed using a THOR dummy model with varying occupant safety system design parameters, such as belt attachment locations, belt load limits, crash pulse, and so on. Third, metamodels were developed using neural networks to predict injury criteria for a given occupant safety system design. Fourth, the occupant safety system was optimized using metamodels, and the optimal design was verified using a subsequent crash simulation. Lastly, the effects of design variables on injury criteria were investigated using the Shapely method. The Euro NCAP score of the THOR dummy model was improved from 14.3 to 16 points. The main improvement resulted from a reduced risk of injury to the chest and leg regions. Higher D-ring and rearward anchor placements benefited the chest and leg regions, respectively, while a rear-loaded crash pulse was beneficial for both areas. The sensitivity analysis through the Shapley method quantitatively estimated the contribution of each design variable regarding improvements in injury metric values for the THOR dummy.

Research on somatosensory shock wave pressure measurement method based on PVDF film

Piezoelectric pressure sensors and human tissue have different pressure impedance coefficients, which results in a discrepancy when accurately measuring the real somatosensory shock wave pressure (SSWP). The aim of this research is to develop a method that can realistically characterize SSWP measurements. To achieve this, the study uses the finite element method to analyze the response of both human tissue and piezoelectric pressure sensors to the same shock wave load. The numerical simulation results show a significant difference in the pressure response between the two under identical shock wave loads. Based on this, the working mode and equivalent model of Polyvinylidene fluoride (PVDF) film for measuring SSWP are determined. Using the finite element method, the same shock wave pressure load is applied to PVDF films with thicknesses of 20 μm, 50 μm, 100 μm, as well as human tissue. The results reveal a good agreement between the pressure response of the PVDF film and human tissue. As the thickness of the PVDF film decreases, particularly at 20 μm thickness, the accuracy improves. Additionally, a comparative experiment is conducted using a bionic dummy model. The outcomes indicate that PVDF film is more stable than piezoelectric pressure sensors and can accurately characterize the real SSWP, aligning with the numerical simulation results by up to 98.4%.

Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health Patients.

Managing mood disorders poses challenges in counseling and drug treatment, owing to limitations. Counseling is the most effective during hospital visits, and the side effects of drugs can be burdensome. Patient empowerment is crucial for understanding and managing these triggers. The daily monitoring of mental health and the utilization of episode prediction tools can enable self-management and provide doctors with insights into worsening lifestyle patterns. In this study, we test and validate whether the prediction of future depressive episodes in individuals with depression can be achieved by using lifelog sequence data collected from digital device sensors. Diverse models such as random forest, hidden Markov model, and recurrent neural network were used to analyze the time-series data and make predictions about the occurrence of depressive episodes in the near future. The models were then combined into a hybrid model. The prediction accuracy of the hybrid model was 0.78; especially in the prediction of rare episode events, the F1-score performance was approximately 1.88 times higher than that of the dummy model. We explored factors such as data sequence size, train-to-test data ratio, and class-labeling time slots that can affect the model performance to determine the combinations of parameters that optimize the model performance. Our findings are especially valuable because they are experimental results derived from large-scale participant data analyzed over a long period of time.

Fundamental Characteristics of Wind Loading on Vaulted-Free Roofs

The present paper investigates the fundamental characteristics of wind loading on vaulted (cylindrical) free roofs based on a wind tunnel experiment and a computational fluid dynamics (CFD) analysis using Large Eddy Simulation (LES). In the wind tunnel experiment, wind pressures at many points, both on the top and bottom surfaces of rigid roof models, were measured in a turbulent boundary layer. The wind tunnel models, including the tubing system installed in the roof and columns, were made using a 3D printer, which made the roof thickness as small as 2 mm, whereas the span B was 150 mm and the length L ranged from 150 to 450 mm. The rise-to-span ratio f/B ranged from 0.1 to 0.4. Pressure taps were installed along the center arc and an arc near the roof edge (verge) of an instrumented model with a length-to-span ratio of L/B = 1. The value of L/B of the tested models was changed from 1 to 3 using one or two dummy models, which had the same configuration as that of the instrumented model but no pressure taps. The wind direction θ was changed from 0° (perpendicular to the eaves) to ±90° (parallel to the eaves). The CFD simulation was carried out only for limited cases, that is, f/B = 0.1 and 0.4 and θ = 0° and 45°, considering the computational time. The effects of f/B, L/B, and θ on the mean (time-averaged) and fluctuating wind pressures acting on the roofs were investigated. In particular, the flow mechanism generating large wind forces on the roof was discussed. An empirical formula was provided for the distribution of mean wind force coefficients along the center arc (Line C) at θ = 0° and 30° and along the edge arc (Line E) at θ = 40° for each f/B ratio. Note that these wind directions provided the maximum and minimum mean wind force coefficients within all wind directions for Lines C and E. Furthermore, the maximum and minimum peak wind force coefficients on the two arcs were presented. The effect of turbulence intensity of approach flow on the maximum and minimum peak wind force coefficients was investigated. The experimental results were compared with those estimated using a peak factor approach, which showed a relatively good agreement between them. The data presented here can be used to guide the design of the main wind force-resisting systems and the cladding/components of vaulted-free roofs.

A modified finite element dummy model of Chinese adult male used for train collision simulations

ABSTRACT This work established a modified finite element (FE) dummy model representing the Chinese 50th percentile males through the whole segment scaling method, referring to the Total Human Model for Safety (THUMS-AM50) of European and American 50th percentile males. The head, neck, chest, abdomen, and knee-thigh-hip (KTH) of the modified model were validated, respectively, by the cadaver experimental results. Integrating the dummy models with a four-car marshalling train collision FE model, we analysed the dynamic response in terms of human body posture, head, and neck injuries of the Chinese 50th percentile males and the European and American 50th percentile males during the frontal train collision process. The corresponding simulation results fitted well with the experimental tests, indicating that the established modified model exerted great biological fidelity. Compared with European-American 50th percentile males, the Von-Mises stress, shear stress, maximum principal strain (MPS), and the cumulative strain damage measure CSDM0.15 of the brain in the Chinese 50th percentile males were approximately higher by 22.21%, 19.85%, 36.58%, and 47.55%, respectively. That meant the Chinese males might be at a higher risk of brain contusion and diffuse axonal injury (DAI) during the train collision. Meanwhile, the Chinese 50th percentile males had more severe neck extension, especially the maximum cervical vertebrae Von-Mises stress and neck injury predictor (Nij) were increased by 30.3% and 50%, respectively. The established modified model could provide a more accurate simulation for predicting the Chinese body injury response during the train collision.

Numerical Analysis of Thorax Injury Caused by the Blunt Impact of SIR-X Sponge Grenade

To effectively assess the injury risk of the blunt impact of the SIR-X sponge grenade on the human thorax, in this paper, we used a numerical simulation technique to test the non-lethal kinetic energy projectiles that blunt impact on the Hybrid III 50th dummy model. By simulating the effect of the L5 projectile on the thorax of the Hybrid III 50th dummy model, about NATO standard AEP-99 (2021 edition), the thoracic displacement curves of the dummy model in three testing conditions were obtained in the validation corridors. The idea of replacing the finite element model of the human body with the Hybrid III 50th dummy finite element model was proposed. We considered the difficulty in obtaining data due to the large deformation of the contact position when the SIR-X sponge grenade impacts the dummy’s thorax. We proposed a mathematical model to predict the impact injury of the human thorax using the rib displacement measured by the rib displacement sensor of the Hybrid III 50th dummy. We simulated the SIR-X sponge grenade blunt impacting the dummy model’s thorax. The measured rib displacement was used to predict and analyze the injury risk of the human thorax, providing a specific data reference for practical application.

Effect of urban neighbourhood layout on the flood intrusion rate of residential buildings and associated risk for pedestrians

Urban neighbourhood layouts affect the flood intrusion rate towards residential buildings through various kinds of damaged openings (doors, windows, gates and shafts) and the associated risk for pedestrians within the urban building complex and ultimately the safety of indoor and outdoor pedestrians in urban flooding events. This study adopts computational fluid dynamics (CFD) to quantify the flood intrusion discharge towards residential buildings and evaluate the flood hazard rating of pedestrians within urban areas of divergent configurations in conjunction with a laboratory flume experiment regarding the stability/instability behaviour of a dummy model that represents a human body in a quasi-natural state. Five types of urban building layouts with three different building densities under three various floodwater conditions, including a determinant type A (see the graphic abstract hereafter), a point group type B, an enclosed type C, a hybrid type D and a new hybrid type E, are examined. The results show that the determinant type A and hybrid type D have a similar trend in terms of the flood intrusion discharge distributions towards each row of buildings and discharge variation with respect to urban building spacing, whereas other urban layouts exhibit different characteristics. Strong floodwater leads to an increased flood risk for pedestrians both outdoors and even indoors within various urban configurations: pedestrians are the most prone to toppling instability on the streets, in turn, behind the building and within the interior of the building. For both determinant type A and hybrid type D, the more pedestrians lie behind the building approaching the upstream, the safer the pedestrians become, while for point group type B, enclosed type C and new hybrid type E, the trend is reversed. The experimental results also offer a novel valuable dataset for the validation of other urban flooding numerical models. This study could be referred to by local authorities and stakeholders to take effective measures to improve the safety of pedestrians and mitigate flood risk in the context of urban planning and urban flood emergency management, such as strengthening flood-resilient urban facility designs and devising optimal routines for emergent evacuation of outdoor pedestrians.

Optimization Study on the Comfort of Human-Seat Coupling System in the Cab of Construction Machinery

The seat of a construction machinery cab is used as the research object. For the current human-seat coupling system comfort research methods and optimization index deficiencies, the seat body pressure comfort and vibration comfort at the same time optimized. Based on the more specialized Toyota 50 percentile dummy model, a human-seat finite element simulation model is established, and the body pressure distribution and vibration response are simulated and calculated. The transverse and longitudinal pressure distributions of the backrest and seat cushion and the pressure map are used to verify the simulation model’s body pressure comfort evaluation indexes. At the same time, the vibration response test is used to verify the vibration comfort evaluation indexes of the simulation model. The test results show that the accuracy of each evaluation index of the established coupling model is greater than 85%, which can provide model support for the subsequent optimization work. In order to improve the comfort of the seat of construction machinery during operation, the hardness of the upper sponge and lower layer sponge is reduced and increased by 10% and 15%, respectively, on the original seat. The body pressure comfort evaluation indexes of the ischium peak pressure, ischium mean pressure, thigh peak pressure and thigh mean pressure are used to evaluate the improved seat. The proposed optimization scheme is to reduce the hardness of the upper sponge and lower layer sponge of the seat cushion by 10% to improve the seat body pressure comfort. Finally, the evaluation indexes of body pressure comfort and vibration comfort are verified by four subjects in an improved seat, and the cushion pressure of different subjects is reduced while the vibration isolation rate is increased, which shows the rationality of the proposed optimization scheme. In addition, the evaluation results of the improved seat are different for subjects of different body sizes, with the most significant improvement for the subject of greater height and weight. The modeling and comfort evaluation methods adopted in the paper can provide a reference for the design and development of the seat.

Comparison of Volunteers' Head Displacement with Computer Simulation-Crash Test with Low Speed of 20 km/h.

Recently, the automotive industry has used simulation programs much more often than experimental research. Computer simulations are more and more often used due to the repeatability of simulation conditions and the possibility of making modifications in simulation objects. Experimental and simulation studies carried out are aimed at developing a model of a simulation dummy adapted to both frontal and rear crash tests, taking into account changes in the moment of resistance in individual joints. The main purpose of the article is to reproduce a real crash test at a low speed of 20 km/h in a simulation program. For this purpose, a series of experimental crash tests with the participation of volunteers was carried out, and then a crash test with a dummy was simulated in the MSC ADAMS program. The experimental studies involved 100 volunteers who were divided into three percentile groups (C5, C50, C95). With the help of force sensors and a high-speed camera, crash tests of volunteers were recorded. The collected data from the force sensors made it possible to map the force in the seat belts. For low-speed crash tests, the displacement and acceleration of individual body parts of the dummy and volunteers can be measured using vision systems. The article identified head displacements of volunteers in the TEMA program based on a video analysis of a crash test film with a frequency of up to 2500 frames per second. The displacement of the simulation dummy's head in the MSC ADAMS program in the considered crash time interval from 0.0 to 0.4 s for all three percentile groups coincided with the head displacement of the volunteers during the experimental crash test.

Endogenous models of binary choice outcomes: Copula-based maximum-likelihood estimation and treatment effects

In this article, I describe the commands that implement the estimation of three endogenous models of binary choice outcome. The command esbinary fits the endogenously switching model, where a potential outcome differs across two treatment states. The command edbinary fits the endogenous dummy model, which includes a dummy variable indicating the treatment state as one of the explanatory variables. After one estimates the parameters of these models, various treatment effects can be estimated as postestimation statistics. The command ssbinary fits the sample-selection model, where an outcome is observed in only one of the states. The commands fit these models using copula-based maximumlikelihood estimation.

A Simulation Study on Electrical and Thermal Properties of Nanofluids Based Mineral Oils for Potential Transformer Applications

The present report demonstrates the efficacy and capabilities of transformer oil due to their growing demand for the production of good insulation. In this work, we have enhanced the electrical and thermal properties of nanofluid (NF)-based mineral oils using the Quickfield simulation in the presence of the different types of nanoparticles (NPs), namely, magnesium oxide (MgO), titanium dioxide (TiO2), and iron oxide (Fe3O4), which are classified based on their conductivity. Different concentrations of NPs of 1%, 5%, and 10% have been used to prepare the NFs. The test cell model and the dummy model of a three-phase transformer have been designed to investigate the electrical and thermal properties of the NFs. It is found that the addition of NPs enhanced both the electrical and thermal properties of the fluid. The voltage at the center of the electrodes decreased by 46% in the case of TiO2 at the highest percentage concentration (10%) of NPs, while for the same concentration of MgO and Fe3O4, it is reduced by 18% and 24%, respectively, whereas the temperature of the oil decreased by approximately 20%, for all NFs at the highest concentration (10%). It is envisaged that the method used can be very useful in determining the properties of NPs before testing them in real life.