Simulation Step Research Articles

Hybrid Optimization-based Cutting Simulation for Soft Objects

Cutting simulation for soft objects is a crucial technology in surgical simulators. The capabilities of a virtual surgery system are determined by the cutting efficiency and simulation performance. Taking both into full consideration, we present a real-time soft object cutting simulation method. The surface-volume model coupling a triangular mesh with a tetrahedral mesh is used as the geometric model. To drive deformable soft objects, we utilize position-based dynamics. The simulation incorporates a flexible progressive cutting technique that updates the topology and produces the cut surface simultaneously with the movement of the virtual scalpel. The incision’s tension and constraint are applied to the simulation steps, ensuring that the incision opens automatically and retains its shape without the need for complicated control. A hybrid optimization is performed to improve the cut mesh and reduce ill-conditioned sliver tetrahedrons while keeping the simulation in parallel. Experiments demonstrate that our method can provide stable and efficient soft object cuttings and the objects can maintain good performance in the subsequent simulation. Additionally, we apply the human slice data to generate real textures for the cut surface and employ a force feedback device to introduce the haptic effect, further enhancing the cutting simulation efficacy.

Dual metallic-based plasmonic back reflector to broaden the absorption spectra of a thin film amorphous silicon solar cell

Here, to obtain high efficiency in a thin film amorphous silicon solar cell, a dual metallic plasmonic back reflector was investigated. The designed dual metal plasmonic back reflector can improve the photocurrent and hence the efficiency. At first, a double layer SiO 2/Si3N4 as the antireflection (AR) was analyzed. The efficiencies of 8.74%, 11.38%, 12.53%, and 13.04% are obtained for a cell without AR, with SiO2, Si3N4, and SiO2/SiN 4 AR layers, respectively. A disk-ring and dual rings-based Ni and Ti-based plasmonic back reflector were designed. The study was carried out by a 3D finite difference time domain method and the optimized parameters were calculated to obtain higher efficiencies. Finally, a relatively higher photocurrent and conversion efficiency of 19.86mA/cm2 and 15.65% were achieved for the optimized structure with a dual Ni rings back reflector, respectively. Because of the importance of amorphous silicon solar cells due to the cost problem of crystalline silicon, here, the simulation steps present a valuable road map to design a novel plasmonic thin-film amorphous silicon solar cell.

Application of dynamic condensation for model order reduction in real-time hybrid simulations

This paper presents an algorithm for model order reduction in real-time hybrid simulations. The bottleneck of hybrid simulations are usually the finite element computations that must be performed in real time. The common approach to deal with this inconvenience is to involve powerful computing hardware. In the following paper opposite approach is presented—a new algorithm is proposed for reducing the model order. This allows to perform hybrid simulations more efficiently while maintaining high accuracy. The algorithm is based on dynamic condensation where the degrees of freedom are divided into masters and slaves, and system matrices are transformed in a way that only masters are kept. The transformation process is complex however, it is performed offline, therefore a relatively high computational effort is made a priori to make real-time calculations more efficient. The dynamic condensation algorithm was adapted to the requirements of hybrid simulations. The proper selection of masters is crucial for accuracy therefore, a novel approach based on evolutionary optimization is implemented. Numerical and experimental examples are provided. The examples prove that by implementing the proposed algorithms the following effects are achieved: (a) the time step of hybrid simulation can be significantly decreased when using implicit integration (increasing the accuracy of the measured dynamic behavior), (b) explicit integration can be sometimes implemented where it was previously not possible in real time, (c) smaller hardware resources can be involved (all computations in real-time hybrid simulations during the experiments were performed on a small microcontroller).

Parameter calculation and result storage for phase-field simulation in α-Mg dendrite growth of Mg-5-wt% Zn alloy

Parameter calculation and result storage, as two necessary steps in phase-field simulation play an important role in ensuring the accuracy of simulation results. A strategy of parameter calculation and result storage is presented for phase-field simulation in α-Mg dendrite growth of Mg-5-wt% Zn alloy under isothermal solidification. Based on the phase diagram and empirical formulas, key parameters of the phase-field model, such as equilibrium partition coefficient k, liquidus slope m, solutal diffusion coefficient in liquid D l, and solutal diffusion coefficient in solid D s, can be obtained. Both structured grid method and structured point method can be used to store simulation results, but using the latter method will reduce about 60% storage space and 37.5% storage time compared with the former. Finally, convergent simulation results of α-Mg dendrite growth are obtained and they are in good agreement with the experimental results about optical micrograph, which verify the accuracy of parameters and stability of storage method.

Improvements of the Brownian walkers method towards the modeling of conduction-radiation coupling

This work directly follows the one presented in a previous article of V. Gonneau, D. Rochais and F. Enguehard (2022) [1]. This contribution describes new results and improvements to existing methods for the modeling of transient thermal conduction within a heterogeneous medium by the movement of Brownian walkers. The material structure is voxelized, and each walker transports an elementary enthalpy during its displacement within the structure. This enthalpy transport associated with the displacement of the walkers represents the conductive flow and makes it possible to simulate transient conduction with a quantitative stochastic approach.This article presents a new method for accounting for Dirichlet type boundary conditions that is quite efficient and that allows to relax quite substantially a constraint of maximum value of the time step of the Brownian walker simulations that had previously been pointed out in [1]. Other boundary condition treatments are also upgraded, in terms of speed (for Neumann type conditions) or generalization (for Robin type conditions). Then, a first non-linear conduction-radiation coupling model in an optically thick and gray semi-transparent medium is solved by Brownian walkers through two approaches: the first one based on a global conductivity function of temperature and allowing to confirm the validity of a stochastic transmission criterion at the interface of two constituents within a heterogeneous medium, and the second one based on the radiative volume power field. This second approach is preceded by the description and the validation of a procedure for the management of a volume power field using Brownian walkers. This procedure introduces the notion of negative Brownian walkers, which prove necessary for representing negative local values of the volume power field as is frequently the case with the radiative volume power.

Oversampling Techniques to Improve the Accuracy of Hardware-in-the-Loop Switching Models

Real-time Hardware-In-the-Loop implementations for power converters involve digital sampling of the on-off signals that are applied to the switches. The most basic way of considering it, is to process only one switch state during a simulation step. This usually causes an incorrect input reading because it can change during the step. The negative effects include the appearance of undesirable subharmonics and numerical inaccuracy. In this work, input signal oversampling is proposed. Thus, several switch states can be properly processed within the same simulation step. The question is how to use this additional information. This paper proposes two oversampling approaches: a sequential one, which is based on previous works, and a parallel implementation, which is the main contribution of the paper. The results obtained with these techniques are compared between them and with the model without oversampling, showing a significant increase in accuracy for both oversampling approaches around 98%. Although the accuracy is very similar in both methods, synthesis results for FPGA implementation are clearly better for the parallel method, which can be easily adapted to process multiple switching events. The final experimental results show a great subharmonic decrease up to 99%.

基于单轴压缩物理试验和虚拟仿真的钙果力学模型构建

The mechanical parameters of Cerasus humilis are the basic data for subsequent studies on fruit deformation, damage, and movement characteristics during harvesting and transportation, but these parameters are rarely reported. Relevant mechanical parameters of whole fruit compression are calculated by comparing physical tests and virtual simulations. The orthogonal rotating combined experimental design was used to arrange the simulation tests, with the elastic modulus (E), yield limit (Ey), and tangent modulus (Et) as the influence factors and compression force as the result. Response surface optimization was employed to find the closest test point to the force–deformation curve of the physical test. The parameters of the pulp test point are as follows: E = 0.923 MPa, Ey = 0.0897 MPa, and Et = 0.478 MPa. Results show that the step on the force–deformation curve was not the beginning of the pulp yield, which was substantially earlier than the strain rate at the simulation step. The region of increased stress in the pulp first appeared at the junction with the core due to stress concentration. Combining virtual and physical tests to solve the mechanical parameters of fruits is more suitable than testing the standard pulp sample.

Numerically efficient two-step CFD simulation model of flow regime and heat transfer for hot water shower sterilizers

This work was carried out to create a numerically efficient validated simulation model for Hot Water Shower (SWS) sterilizers. The goal of the work was to achieve a more homogeneous temperature and water distribution inside the sterilizers developed in the future. A lab-scale test bench of an SWS sterilizer with a configurable water volume flow rate and temperature was designed to validate the Computational Fluid Dynamics (CFD) model that was created. The heating and cooling phases at water volume flow rates of 20 and 40m3/h per m2 spraying surface were analyzed. Additionally, the flow and film regime were studied. The CFD model was split into two simulation steps to significantly improve the numerical efficiency. The novel two-step approach developed is computationally 1800 times faster as compared with a complete sterilization cycle than a state-of-the-art approach. The simulated temperature of the test load was in good accordance with the experimental measurements. The flow regime was largely accurately replicated. Overall, the created validated CFD model is suitable for upscaling to an industry-sized SWS sterilizer due to its numerical efficiency.

Risk Quantification and Visualization Method for Loss-of-Control Scenarios in Flight

This paper proposes a flight risk analysis method that combines risk assessment and visual deduction to study the causes of flight accidents, specifically the loss of control caused by failure factors. The goal is to explore the impact of these failure factors on loss-of-control events and illustrate the risk evolution under different scenarios in a clear and intuitive manner. To achieve this, the paper develops a failure scenario tree to guide flight simulations under different loss-of-control scenarios. The next step involves developing a multi-parameters risk assessment method that can quantify flight risk at each time step of the flight simulation. This assessment method uses entropy weight and a grey correlation algorithm to assign variable weights to the different parameters. Finally, the paper presents the visual deduction of the risk evolution process under different loss-of-control scenarios using a risk tree that concisely represents the time-series risk assessment results and failure logical chains. Taking three common failure factors (actuator failure, engine failure, and wing icing) as cases, the paper designs 25 different loss-of-control scenarios to demonstrate the flight risk analysis method. By comparing the risk evolution process under different loss-of-control scenarios, the paper explores the impact of the failure factors on flight safety. The analysis results indicate that this method combines risk analysis from both individual and global perspectives, enabling effective analysis of risk evolution in loss-of-control events.

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

Abstract. Climate change and increased fire are eroding the resilience of boreal forests. This is problematic because boreal vegetation and the cold soils underneath store approximately 30 % of all terrestrial carbon. Society urgently needs projections of where, when, and why boreal forests are likely to change. Permafrost (i.e., subsurface material that remains frozen for at least 2 consecutive years) and the thick soil-surface organic layers (SOLs) that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and SOL module named the Permafrost and Organic LayEr module for Forest Models (POLE-FM) that operates at fine spatial (1 ha) and temporal (daily) resolutions. The module mechanistically simulates daily changes in depth to permafrost, annual SOL accumulation, and their complex effects on boreal forest structure and functions. We coupled the module to an established forest landscape model, iLand, and benchmarked the model in interior Alaska at spatial scales of stands (1 ha) to landscapes (61 000 ha) and over temporal scales of days to centuries. The coupled model generated intra- and inter-annual patterns of snow accumulation and active layer depth (portion of soil column that thaws throughout the year) generally consistent with independent observations in 17 instrumented forest stands. The model also represented the distribution of near-surface permafrost presence in a topographically complex landscape. We simulated 39.3 % of forested area in the landscape as underlain by permafrost, compared to the estimated 33.4 % from the benchmarking product. We further determined that the model could accurately simulate moss biomass, SOL accumulation, fire activity, tree species composition, and stand structure at the landscape scale. Modular and flexible representations of key biophysical processes that underpin 21st-century ecological change are an essential next step in vegetation simulation to reduce uncertainty in future projections and to support innovative environmental decision-making. We show that coupling a new permafrost and SOL module to an existing forest landscape model increases the model's utility for projecting forest futures at high latitudes. Process-based models that represent relevant dynamics will catalyze opportunities to address previously intractable questions about boreal forest resilience, biogeochemical cycling, and feedbacks to regional and global climate.

Crystal morphology prediction of CL-20 and 1,4-DNI co-crystal at different temperatures.

The morphologies of hexanitrohexaazaisowurtzitane (CL-20) and 1,4-dinitroimidazole (1,4-DNI) co-crystal under vacuum or solvent at different temperatures were predicted. The CL-20/1,4-DNI co-crystal has six important growth crystal planes: (002), (011), (101), (11‒1), (110), (111). The areas of (002), (101), and (011) planes account for a relatively large proportion, which are important crystal planes that affect the crystal morphology. The crystal habits at different temperatures were simulated. The simulation results showed that the crystal plane attachment energy of CL-20 and 1,4-DNI co-crystal increases with the increase of temperature, indicating that the increase of temperature is conducive to the growth of crystal planes. The aspect ratio decreases with the increase of temperature and the morphology of co-crystal becomes more spherical at a higher temperature. The theoretical predictions are in good agreement with the experiment. The simulation results can provide guidance for the crystallization of CL-20/1,4-DNI to obtain a nearly spherical crystal morphology. The CL-20/1,4-DNI unit cell structure was geometrically optimized by the COMPASS force field. The AE model was used to predict the morphology of CL-20/1,4-DNI under vacuum, resulting in the most morphologically important growth planes. Ethyl acetate was selected as the solvent. The interaction energy between the solvent and the crystal plane, and the attachment energies in solvent at 298 K, 320 K, 340 K, 360 K, and 380 K were predicted. The NVT ensemble is used in the molecular dynamics calculation process. The simulation step is 1 fs and the total simulation time is 500 ps. The Andersen thermostat is selected as the temperature control method. In the potential energy calculation, the atom-based and Ewald methods were selected to calculate the van der Waals force and the electrostatic interaction force, respectively.

Improvement of Relative DEM Time Step Range in Fast Fluidization Simulation of Type-A FCC Particles

In many process engineering fields, gas-particle fluidized beds are widely used. In fluidized bed research, the discrete element method, or DEM, has been a powerful tool for design and operation purposes. However, with the use of Type-A powders, fluid catalytic cracking or FCC particles being classical cases, they have hardly been reported in DEM simulations of fast fluidization. This study paid close attention to the suitable selection of a stiffness constant and a DEM time step. To reflect their respective effects and complicated interactions, a so-called relative DEM time step was defined. The drag coefficient was correlated using the energy-minimization multi-scale (EMMS) approach to reasonably calculate the gas–solid interaction. Six representative cases with different relative time step values were chosen to simulate a micro-fluidized bed of Type-A FCC powders. The results showed that DEM employing EMMS-based drag force was able to greatly enlarge the suitable range of relative time steps in a fast fluidization simulation of Type-A powders. In addition, the typical macro flow structures of fast fluidization was successfully captured: axially dilute in the top and dense in the bottom, and radially dilute in the core and dense near the wall. Moreover, the distinct gas–solid backmixing, which is considered one of the most important pieces of evidence for the determination of fast fluidization regimes, was modeled. It was indicated that the EMMS-based drag model attenuated the overestimated drag force so that the soft-sphere contact model would be able to more appropriately deal with particle collision, and thus improve the suitable relative DEM time step range.

Exceptional and innovational analysis of n-CdS/p-Si solar cells based on software packages and bias point models: insights into theoretical and experimental characteristics of fabricated solar cells

The characteristics of a single solar cell made by CdS thin film deposition on a silicon glass substrate were estimated using simulation models in this study. An aluminum electrode was attached to a silicon wafer to produce a heterojunction, and the indium fingers were fashioned into another electrode and connected directly to the CdS layer. Simulation steps were performed using PV*SOL 3.0 software package and bias points (ISC, VOC ) models. In addition to the use of advanced programs such as MATLAB software (Shell SQ150 PV module), Mathcad 2000 program, and Origin Lab 2019 program.Simulation programs for extracting photovoltaic parameters have been executed together with the laboratory procedures. The simulation programs and experimental procedures aimed in general to know the (current-voltage) and (power-voltage) characteristics of the studied single-diode photovoltaic.

Passenger flow simulation of Xiamafang metro station based on AnyLogic

In this paper, based on the functional location layout and passenger flow distribution characteristics of Xiamafang metro station, the passenger flow of Xiamafang metro station is simulated and analyzed with the help of the traffic behavior model theory of pedestrians by using the AnyLogic micro dynamic simulation software, the traffic behavior, simulation method and simulation effect are studied. Firstly, it introduces the actual situation of Xiamafang metro station, including the analysis of station layout and passenger flow organization streamline. Secondly, the pedestrian micro simulation model and implementation method are studied, including the social force model, the introduction of AnyLogic software and the implementation steps of pedestrian simulation. Finally, in the case of simplifying the layout of facilities in Xiamafang metro station, the simulation model of subway station is established by using AnyLogic software, the simulation effect is studied, the main problems of passenger flow in the station are analyzed, and the optimization measures are put forward for the bottleneck problems, which provides the basis for the actual operation and management decision-making.

Component-Oriented Modeling Method for Real-Time Simulation of Power Systems

This paper proposes a component-oriented modeling method for power system simulation, which optimizes the modeling process of the FPGA-based real-time digital simulator (FRTDS) to enhance its computational efficiency. In this paper, a component modeling method for various types of elements in the power system is presented, which makes the modeling process in FRTDS more user-friendly and highly scalable. By applying the concepts of combination and reconstruction of components to electrical components, the component-oriented modeling method becomes better suited for combined elements with fixed connection modes and elements that require online model replacement in the power system. Utilizing the characteristics of component-oriented modeling, the variable declaration structure and node elimination strategy in the simulation script are optimized, enabling the simulation script to fit better with the hardware structure of FRTDS. Additionally, a substation is simulated in FRTDS with a simulation step size of 50 µs, thus verifying the correctness of the component-oriented modeling method and its ability to improve the computational power of FRTDS.

Digital twin of an absorption chiller for solar cooling

The aim of this study is to create a digital twin of a commercial absorption chiller for control and optimization purposes. The chiller is a complex system that is affected by solar intermittency and non-linearities. The authors use Adaptive Neuro-fuzzy Inference System (ANFIS) to model the chiller’s behavior during transients and part-load events. The chiller is divided into four sub-models, each modeled by ANFIS, and trained and validated using data from 15 days of operation. The ANFIS models are precise, accurate, and fast, with a worst-case Mean Absolute Percentage Error (MAPE) of 3.30% and reduced error dispersion (σE=0.88) and Standard Error (SE=0.01). The models outperformed literature models in terms of MAPE, with MAPEs of 1.12%, 2.21%, and 3.24% for the High Temperature Generator (HTG), absorber + condenser, and evaporator outlet temperatures, respectively. The computational execution time of the model is also a valuable asset, with an average simulation step taking less than 0.20 ms and a total simulation time of 8.9 s for three days of operation. The resulting digital twin is suitable for Model Predictive Control applications and fast what-if analysis and optimization due to its gray-box representation and computational speed.

A Control Method for Water Cannon of Unmanned Fireboats Considering Wind and Ship Motion Disturbances

In order to realize accurate and fast firefighting at sea, a control method for water cannons of unmanned fireboats considering wind and ship motion disturbances is presented. This method combines information fusion, computer vision, and prediction technology based on neural network. Firstly, a prediction model of the jet trajectory of the fire water cannon considering the disturbances of constant horizontal wind is established, and the effective range of the water cannon’s angles under the target working environment is obtained. Secondly, fusing the visual recognition information and predicted ship motion attitudes information, a double adaptive fuzzy controller is designed to compensate for the disturbances caused by the change in ship motion attitudes. Meanwhile, the online particle swarm optimization (PSO) is applied to fuzzy control to improve operational accuracy while enhancing the ability to adapt to environmental changes. The proposed control method was experimentally verified. As a result, the adaptive fuzzy controller based on the PSO can self-adjust the parameters to adapt to the changes in the working environment within 0.6 s, and the efficiency is improved by about 20%∼50% compared with the traditional fuzzy control. The double adaptive fuzzy control can reach a stable and effective working state within 10 simulation steps, and the RMSE of the drop point error is only 3 ×10−3 m for 40 simulation steps after stabilization, which can effectively resist disturbances and improve efficiency and control accuracy. The control method can provide a practical reference for engineering applications of water cannon control of unmanned fireboats.

A multi-step approach for reliability-based robust design optimization of truss structures

There are two general methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) for the optimal design of structures with non-deterministic variables. In the problem-solving process of both RDO and RBRDO, assessing the probabilistic constraints of the problem and the standard deviation of the structural responses is time-consuming and costly. In this study, by presenting a multi-step approach, for a probable optimal solution, the deterministic constraints are first investigated. Then the limit state functions related to probabilistic constraints are computed based on the mean value of random variables (in the RBRDO problem) and in the step of uncertainties effects simulation on the response of the structure, probabilistic constraints are evaluated (in the RBRDO problem). Designs that not meeting the deterministic constraints or in the unsafe area for the mean values of the random variables are not included in calculating the first and second terms of the objective function and reliability assessment. This leads to reduce the volume of calculations. The Monte Carlo simulation method is used to assess the probabilistic constraints, and the EVPS metaheuristic algorithm is used for the optimization process. Three benchmark trusses of 10, 25, and 72 bars were studied to assess the efficiency of the proposed approach. The first objective function in these problems was the mean weight of trusses and the second objective function was the standard deviation of the displacement of a specific node in a certain direction.

Local chemical inhomogeneities in TiZrNb-based refractory high-entropy alloys

(1) The local chemical order features in the TiZrNb-based alloys are as follows: (i) For the TiZrNb alloy, the Ti-Zr pair is the most favored, while there exists relatively weaker Nb-Nb pair; (ii) For the TiZrHfNb alloy, Ti and Nb prefer to pair with Zr and Hf, respectively; (iii) For TiZrHfNbTa, Ta is prone to form sub-nanoscale segregation, in addition to the existing chemical preference among Ti, Zr, Hf and Nb. (2) Accompanying the LCO, there exists compositional undulation in the TiZrHfNb alloy on nanometer scale, arising from the preferred local enrichment of [(Ti, Zr)] or [(Hf, Nb)] CSROs. (3) The local chemical inhomogeneity evolves strongly with temperature, from the RSS structure at high temperatures to the pronounced tendency of forming chemically favored pairs at low temperatures. The LCO develops beyond the range of CSRO, to a characteristic length scale of at least one nanometer. (4) The predicted yield strengths of the RSS samples are generally lower than the experimental values by ∼ 100 MPa, while those calculated for CSRO-containing samples approach the experimental measurements. This strongly suggests the need to take into account the contribution of CSRO (and/or other local chemical inhomogeneities) to achieve a more accurate prediction of the yield strength of TiZrNb-based bcc HEAs. (5) When the strong CSRO-promoting Ti is replaced by Ta, the resultant TaZrHfNb alloy is found to contain only a weak degree of local chemical order, unlike the three representative TiZrNb-based HEAs in the present study. (6) Our work reveals the trend of the chemical inhomogeneities and compositional undulation that would develop as intrinsic features in these TiZrNb-based bcc HEAs. Meanwhile, the CSRO tendency also sheds light on the fertile emergence of (Ti,Zr,O)- complexes that form upon the addition of oxygen/nitrogen into such HEAs to purposely accentuate (sub)nanometer-scale chemical complexes/heterogeneities. Multi-principal element solid solutions are prone to develop local chemical inhomogeneities, i.e. , chemical order/clustering and/or compositional undulation. However, these structural details from short-range (first couple of nearest-neighbor atomic shells) to nanometer length scale are very challenging to resolve in both experimental characterization and computer simulations. For instance, Monte Carlo modeling based on density-functional-theory calculations is severely limited by the sample size and the simulation steps practical in the simulations. Adopting the cluster expansion approach, here we systematically reveal the local chemical inhomogeneity, including chemical order and compositional fluctuation, in three representative equiatomic TiZrNb-based body-centered cubic refractory high-entropy alloys (HEAs): TiZrNb, TiZrHfNb and TiZrHfNbTa. Ti-Zr pairs are found to exhibit the highest degree of chemical preference among all atomic pairs. Such chemical short-range order (CSRO) induces an accompanying compositional undulation, both extending to characteristic dimensions of the order of one nanometer. The chemical inhomogeneity trend uncovered for this series of TiZrNb-based HEAs is expected to impact their mechanical properties; e.g. , incorporating the CSRO effects in a current model significantly improves its agreement with experimental measured yield strength.

Development of a novel footwear based power harvesting system

Daily activities such as walking and running possess abundant amount of energy, which is usually wasted and have the potential to be harvested. Especially, the energy generated from footsteps, if tapped appropriately, may be useful for charging electronic devices such as cell phones, wearables, and medical devices. In this study, the kinetic energy from footsteps was captured using a novel six-layered compartmental insole design with embedded piezoelectric transducers. This system was fabricated using additive manufacturing techniques and evaluated for its capabilities to charge a battery while walking and running. The charging performance was estimated initially for 6000 walking steps and extended to approximately 67,000 simulated running steps to fully charge the battery. A range of transducer arrangements were tested, indicating better power generation from the parallel combinations compared to series. Across gait activities, running was observed to lead to better coordination between the piezoelectric transducers and generation of higher power, compared to in walking. While very high amount of electrical power was not realized, the device performance was found to be satisfactory to charge low power rated wearable lifestyle electronic or medical devices. The findings from this work is anticipated to provide novel insights for power harvesting from human gait.