scholarly journals Prediction and Validation of Landing Stability of a Lunar Lander by a Classification Map Based on Touchdown Landing Dynamics’ Simulation Considering Soft Ground

Aerospace ◽  
2021 ◽  
Vol 8 (12) ◽  
pp. 380
Author(s):  
Yeong-Bae Kim ◽  
Hyun-Jae Jeong ◽  
Shin-Mu Park ◽  
Jae Hyuk Lim ◽  
Hoon-Hee Lee
Keyword(s):  
Friction Coefficient ◽  
Soft Soil ◽  
Slope Angle ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Soft Ground ◽  
Fe Model ◽  
Machine Learning Classification ◽  
Lunar Lander ◽  
Stable Sliding

In this paper, a method for predicting the landing stability of a lunar lander by a classification map of the landing stability is proposed, considering the soft soil characteristics and the slope angle of the lunar surface. First, the landing stability condition in terms of the safe (=stable), sliding (=unstable), and tip-over (=statically unstable) possibilities was checked by dropping a lunar lander onto flat lunar surfaces through finite-element (FE) simulation according to the slope angle, friction coefficient, and soft/rigid ground, while the vertical touchdown velocity was maintained at 3 m/s. All of the simulation results were classified by a classification map with the aid of logistic regression, a machine-learning classification algorithm. Finally, the landing stability status was efficiently predicted by Monte Carlo (MC) simulation by just referring to the classification map for 10,000 input datasets, consisting of the friction coefficient, slope angles, and rigid/soft ground. To demonstrate the performance, two virtual lunar surfaces were employed based on a 3D terrain map of the LRO mission. Then, the landing stability was validated through landing simulation of an FE model of a lunar lander requiring high computation cost. The prediction results showed excellent agreement with those of landing simulations with a negligible computational cost of around a few seconds.

scholarly journals Adaptive Surrogate Modeling for Efficient Coupling of Musculoskeletal Control and Tissue Deformation Models

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Jason P. Halloran ◽  
Ahmet Erdemir ◽  
Antonie J. van den Bogert
Keyword(s):  
Surrogate Model ◽  
Reaction Force ◽  
Computational Cost ◽  
Surrogate Modeling ◽  
Tissue Mechanics ◽  
Dynamics Simulation ◽  
Von Mises Stress ◽  
Integration Step ◽  
Fe Model ◽  
Jump Height

Finite element (FE) modeling and multibody dynamics have traditionally been applied separately to the domains of tissue mechanics and musculoskeletal movements, respectively. Simultaneous simulation of both domains is needed when interactions between tissue and movement are of interest, but this has remained largely impractical due to the high computational cost. Here we present a method for the concurrent simulation of tissue and movement, in which state of the art methods are used in each domain, and communication occurs via a surrogate modeling system based on locally weighted regression. The surrogate model only performs FE simulations when regression from previous results is not within a user-specified tolerance. For proof of concept and to illustrate feasibility, the methods were demonstrated on an optimization of jumping movement using a planar musculoskeletal model coupled to a FE model of the foot. To test the relative accuracy of the surrogate model outputs against those of the FE model, a single forward dynamics simulation was performed with FE calls at every integration step and compared with a corresponding simulation with the surrogate model included. Neural excitations obtained from the jump height optimization were used for this purpose and root mean square (RMS) difference between surrogate and FE model outputs (ankle force and moment, peak contact pressure and peak von Mises stress) were calculated. Optimization of the jump height required 1800 iterations of the movement simulation, each requiring thousands of time steps. The surrogate modeling system only used the FE model in 5% of time steps, i.e., a 95% reduction in computation time. Errors introduced by the surrogate model were less than 1mm in jump height and RMS errors of less than 2N in ground reaction force, 0.25Nm in ankle moment, and 10kPa in peak tissue stress. Adaptive surrogate modeling based on local regression allows efficient concurrent simulations of tissue mechanics and musculoskeletal movement.

A two-stage design optimization framework for multifield origami-inspired structures

2021 ◽  
pp. 1045389X2110116
Author(s):  
Wei Zhang ◽  
Saad Ahmed ◽  
Jonathan Hong ◽  
Zoubeida Ounaies ◽  
Mary Frecker
Keyword(s):  
Case Studies ◽  
Computing Time ◽  
Computational Cost ◽  
High Fidelity ◽  
Fe Model ◽  
Two Stage ◽  
Baseline Design ◽  
Optimization Framework ◽  
Highly Nonlinear ◽  
Stage 1

Different types of active materials have been used to actuate origami-inspired self-folding structures. To model the highly nonlinear deformation and material responses, as well as the coupled field equations and boundary conditions of such structures, high-fidelity models such as finite element (FE) models are needed but usually computationally expensive, which makes optimization intractable. In this paper, a computationally efficient two-stage optimization framework is developed as a systematic method for the multi-objective designs of such multifield self-folding structures where the deformations are concentrated in crease-like areas, active and passive materials are assumed to behave linearly, and low- and high-fidelity models of the structures can be developed. In Stage 1, low-fidelity models are used to determine the topology of the structure. At the end of Stage 1, a distance measure [Formula: see text] is applied as the metric to determine the best design, which then serves as the baseline design in Stage 2. In Stage 2, designs are further optimized from the baseline design with greatly reduced computing time compared to a full FEA-based topology optimization. The design framework is first described in a general formulation. To demonstrate its efficacy, this framework is implemented in two case studies, namely, a three-finger soft gripper actuated using a PVDF-based terpolymer, and a 3D multifield example actuated using both the terpolymer and a magneto-active elastomer, where the key steps are elaborated in detail, including the variable filter, metrics to select the best design, determination of design domains, and material conversion methods from low- to high-fidelity models. In this paper, analytical models and rigid body dynamic models are developed as the low-fidelity models for the terpolymer- and MAE-based actuations, respectively, and the FE model of the MAE-based actuation is generalized from previous work. Additional generalizable techniques to further reduce the computational cost are elaborated. As a result, designs with better overall performance than the baseline design were achieved at the end of Stage 2 with computing times of 15 days for the gripper and 9 days for the multifield example, which would rather be over 3 and 2 months for full FEA-based optimizations, respectively. Tradeoffs between the competing design objectives were achieved. In both case studies, the efficacy and computational efficiency of the two-stage optimization framework are successfully demonstrated.

scholarly journals Numerical Modeling and Safety Design for Lithium-Ion Vehicle Battery Modules Subject to Crush Loading

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 118
Author(s):  
Feng Zhu ◽  
Runzhou Zhou ◽  
David J. Sypeck
Keyword(s):  
Failure Modes ◽  
Computational Study ◽  
Short Circuit ◽  
Computational Cost ◽  
Lithium Ion ◽  
Simplified Model ◽  
Homogeneous Material ◽  
Fe Model ◽  
Safety Design ◽  
Battery Module

In this work, a computational study was carried out to simulate crushing tests on lithium-ion vehicle battery modules. The tests were performed on commercial battery modules subject to wedge cutting at low speeds. Based on loading and boundary conditions in the tests, finite element (FE) models were developed using explicit FEA code LS-DYNA. The model predictions demonstrated a good agreement in terms of structural failure modes and force–displacement responses at both cell and module levels. The model was extended to study additional loading conditions such as indentation by a cylinder and a rectangular block. The effect of other module components such as the cover and cooling plates was analyzed, and the results have the potential for improving battery module safety design. Based on the detailed FE model, to reduce its computational cost, a simplified model was developed by representing the battery module with a homogeneous material law. Then, all three scenarios were simulated, and the results show that this simplified model can reasonably predict the short circuit initiation of the battery module.

scholarly journals A thermal resistances-based approach for thermal-elastohydrodynamic calculations in point contacts

2017 ◽  
Vol 232 (11) ◽  
pp. 2088-2102 ◽  
Author(s):  
Eduardo de la Guerra Ochoa ◽  
Javier Echávarri Otero ◽  
Enrique Chacón Tanarro ◽  
Benito del Río López
Keyword(s):  
Friction Coefficient ◽  
Film Thickness ◽  
Thermal Effects ◽  
Good Accuracy ◽  
Computational Cost ◽  
Point Contact ◽  
Elastohydrodynamic Lubrication ◽  
Point Contacts ◽  
New Approach ◽  
Ball On Disc

This article presents a thermal resistances-based approach for solving the thermal-elastohydrodynamic lubrication problem in point contact, taking the lubricant rheology into account. The friction coefficient in the contact is estimated, along with the distribution of both film thickness and temperature. A commercial tribometer is used in order to measure the friction coefficient at a ball-on-disc point contact lubricated with a polyalphaolefin base. These data and other experimental results available in the bibliography are compared to those obtained by using the proposed methodology, and thermal effects are analysed. The new approach shows good accuracy for predicting the friction coefficient and requires less computational cost than full thermal-elastohydrodynamic simulations.

Research to build technological procedure for soft ground improvement using sea sand-cement-fly ash column

2020 ◽  
Vol 61 (HTCS6) ◽  
pp. 1-9
Author(s):  
Thinh Duc Ta ◽  
Phuc Dinh Hoang ◽  
Thang Anh Bui ◽  
Trang Huong Thi Ngo ◽  
Diu Thi Nguyen ◽  
...  
Keyword(s):  
Fly Ash ◽  
Load Capacity ◽  
Ground Improvement ◽  
Soft Soil ◽  
Soil Reinforcement ◽  
Soft Ground ◽  
Design Calculation ◽  
Sea Sand ◽  
Composite Ground ◽  
Soft Ground Improvement

Sea sand-cement-fly ash column technology for soft soil treatment is a new technology in the process of completing the theoretical basis, the experimental basis, and the construction of the ground treatment technological procedure. The paper presents the results of scientific research on design, calculation, construction, and acceptance of sea sand-cement-fly ash column. The scientific basis for the design of column is to consider the role of the column in composite ground, that is to use the column as soft ground improvement or soft soil reinforcement. The important parameters for the column design are: cement and fly ash content; column length; column diameter; number of columns; distance among columns; load capacity and settlement of composite ground. The sequence of steps of construction and acceptance of column includes: selection of construction equipment, preparation of construction sites, trial construction, official construction, evaluation of ground quality after treatment and preparation of document for acceptance.

Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111)

2021 ◽  
Author(s):  
Kai Xu ◽  
Lei Yan ◽  
Bingran You
Keyword(s):  
Molecular Dynamics ◽  
Active Learning ◽  
Force Field ◽  
Density Functional ◽  
Process Model ◽  
Large Scale ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Potential Energy Landscape ◽  
Three Body

Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions. Most energy models are limited by a fundamental tradeoff between accuracy and speed. Although ab initio MD based on density functional theory (DFT) has high accuracy, its high computational cost prevents its use for large-scale and long-timescale simulations. Here, we use Bayesian active learning to construct a Gaussian process model of interatomic forces to describe Pt deposited on Ag(111). An accurate model is obtained within one day of wall time after selecting only 126 atomic environments based on two- and three-body interactions, providing mean absolute errors of 52 and 142 meV/Å for Ag and Pt, respectively. Our work highlights automated and minimalistic training of machine-learning force fields with high fidelity to DFT, which would enable large-scale and long-timescale simulations of alloy surfaces at first-principles accuracy.

Molecular Dynamics Simulation of AFM-Based Nanomachining Processes

2011 ◽  
Author(s):  
Rapeepan Promyoo ◽  
Hazim El-Mounayri ◽  
Kody Varahramyan ◽  
Ashlie Martini
Keyword(s):  
Molecular Dynamics ◽  
Friction Coefficient ◽  
Md Simulation ◽  
Computational Models ◽  
Dynamics Simulation ◽  
Radius Of Curvature ◽  
Force Microscopy ◽  
Indentation Force ◽  
Atomic Force ◽  
Development And Validation

Recently, atomic force microscopy (AFM) has been widely used for nanomachining and fabrication of micro/ nanodevices. This paper describes the development and validation of computational models for AFM-based nanomachining (nanoindentation and nanoscratching). The Molecular Dynamics (MD) technique is used to model and simulate mechanical indentation and scratching at the nanoscale in the case of gold and silicon. The simulation allows for the prediction of indentation forces and the friction force at the interface between an indenter and a substrate. The effects of tip curvature and speed on indentation force and friction coefficient are investigated. The material deformation and indentation geometry are extracted based on the final locations of atoms, which are displaced by the rigid tool. In addition to modeling, an AFM was used to conduct actual indentation at the nanoscale, and provide measurements to validate the predictions from the MD simulation. The AFM provides resolution on nanometer (lateral) and angstrom (vertical) scales. A three-sided pyramid indenter (with a radius of curvature ∼ 50 nm) is raster scanned on top of the surface and in contact with it. It can be observed from the MD simulation results that the indentation force increases as the depth of indentation increases, but decreases as the scratching speed increases. On the other hand, the friction coefficient is found to be independent of scratching speed.

scholarly journals Experimental application of optimal depth of PVDs determination under vacuum loading condition

2016 ◽  
Vol 19 (1) ◽  
pp. 116-121
Author(s):  
Nhat Dai Vo ◽  
Viet Hoang Quoc Lam ◽  
Tuan Minh Pham
Keyword(s):  
Loading Condition ◽  
Ground Improvement ◽  
Soft Soil ◽  
Small Error ◽  
Soft Ground ◽  
Optimal Depth ◽  
Geological Feature ◽  
Experimental Application ◽  
Technical Requirements ◽  
Soft Ground Improvement

Viet Nam is one of the country that has a very soft and complicated geological feature. Therefore, how to economize cost but satisfy the standard and technical requirements in designing by selecting an appropriate method in building especially projects constructed on soft ground is always needed to consider and research continuouslly. In this paper, a method how to determine the optimal depth of PVDs under vacuum loading condition for soft ground improvement is presented and applied to specific case in 861 provincial street, Ward Cai Be, Tien Giang District. The soft soil includes two layers with total 12m thick and is allowed to drain on the top and bottom faces (double drainage). The result shows that the optimal depth of PVDs is about 10,5m with the small error of 0,7%

scholarly journals Comparisons Between Braking Experiments and Longitudinal Train Dynamics Using Friction Coefficient and Braking Pressure Modeling in a Freight Train

2020 ◽  
Vol 14 (1) ◽  
pp. 154-163
Author(s):  
Don Bum Choi ◽  
Rag-Gyo Jeong ◽  
Yongkook Kim ◽  
Jangbom Chai
Keyword(s):  
Friction Coefficient ◽  
Time Integration ◽  
Expansion Method ◽  
Dynamics Simulation ◽  
Dynamic Simulations ◽  
Freight Train ◽  
Emergency Braking ◽  
Braking Distance ◽  
Train Dynamics ◽  
Simulation Results

Background: This paper describes the predictions and validation of the pneumatic emergency braking performance of a freight train consisting of a locomotive and 20 wagons, generally operated in Korea. It suggests the possibility of replacing the expensive and time-consuming train running tests with longitudinal train dynamic simulations. Methods: The simulation of longitudinal train dynamics of a freight train uses the time integration method of EN 14531. For reasonable simulation results, the characteristics of the train and brake equipment must be considered. For the train characteristics, specifications provided by the vehicle manufacturer are used. The braking characteristics are analyzed by friction coefficient tests and a braking pressure model. The friction coefficients of a locomotive and wagons are tested with a dynamo test bench and statistically expanded to account for variability. Freight trains should take into account the braking delay time. To reflect this in the simulation, the brake cylinder pressure pattern model uses pressures and exponential empirical equations measured at selective positions in a train of 50 vehicles. The simulation results are validated in comparison with those of the braking tests of a freight train consisting of 1 locomotive and 20 wagons. Results: The results of the longitudinal dynamics simulation show very similar results to the running test results based on the speed profile and braking distance. Conclusion: In particular, the statistical expansion method of the friction coefficient enables robust prediction of the distribution of the braking distance. The simulation can reduce or make up for costly and time-consuming repeated braking tests and reduce the risks that may arise during testing.

Two-Stage Structural Damage Assessment by Combining Modal Kinetic Energy Change with Symbiotic Organisms Search

2019 ◽  
Vol 19 (10) ◽  
pp. 1950120 ◽  
Author(s):  
D. Dinh-Cong ◽  
T. Nguyen-Thoi ◽  
M. Vinyas ◽  
Duc T. Nguyen
Keyword(s):  
Kinetic Energy ◽  
Damage Assessment ◽  
Structural Damage ◽  
Heuristic Algorithms ◽  
Computational Cost ◽  
Energy Change ◽  
Fe Model ◽  
Two Stage ◽  
Symbiotic Organisms Search ◽  
Symbiotic Organisms

In the literature, modal kinetic energy (MKE) has been commonly utilized for optimal sensor placement strategies. However, there have been very few studies on its application to structural damage detection. This paper introduces a new two-stage structural damage assessment method by combining the modal kinetic energy change ratio (MKECR) and symbiotic organisms search (SOS) algorithm. In the first stage, an efficient damage indicator, named MKECR, is used to locate the potential damaged sites. Meanwhile, for the purpose of comparison with MKECR, three other indices are also used. In the second stage, an SOS-based finite element (FE) model updating strategy is adopted to estimate the damage magnitude of identified sites, while excluding false warnings (if any), where an objective function is proposed using a combination of the flexibility matrix and modal assurance criterion (MAC). The performance of the SOS algorithm is also verified by comparing with four other meta-heuristic algorithms. Finally, three numerical examples of 2D truss and frame structures with various hypothetical damage scenarios are carried out to investigate the capability of the proposed method. The numerical results indicate that the proposed method not only can accurately locate and quantify single- and multi-damage in the structures, but also shows a great saving in computational cost.

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