Studies on Headform Impact Design

2001 ◽  
Author(s):  
Anindya Deb
Keyword(s):  
Current Model ◽  
Relative Effectiveness ◽  
Trial And Error ◽  
Worst Case ◽  
New Approach ◽  
Geometrical Properties ◽  
Head Injury Criterion ◽  
Kinematic Relationship ◽  
Safety Compliance ◽  
Energy Absorbing

Abstract HIC(d) (Head Injury Criterion, dummy) is defined as a kinematic relationship involving resultant translational deceleration at the CG (center of gravity) of a biofidelic headform and duration of contact. As deceleration response of a headform is in general a function of the energy-absorbing and geometrical properties of an obstructing structure (for a given impact speed), HIC(d) can be expressed, at least symbolically, as a function of those properties. The current paper uses a simplified mathematical model to capture the worst case of headform impact as considered in the FMVSS 201 regulation for upper interior head impact. The obstructing structural countermeasure in the path of a colliding headform is assumed to possess idealized elastoplastic although physically relevant behavior under loading. During the process of designing for headform impact safety compliance, which often turns out to be a trial-and-error process, it is sometimes difficult to see the correspondence between HIC(d) and the relative effectiveness of design iterations in terms of energy-absorption. Thus, relationship between HIC(d) and energy absorbed by such structural countermeasures is investigated. Based on results obtained from the current model and a new approach, an explicit relationship is derived between HIC(d) and the characteristic properties of an energy-absorbing countermeasure that can be used as a design aid.

scholarly journals Inundation mapping based on reach-scale effective geometry

2018 ◽  
Vol 22 (11) ◽  
pp. 5967-5985 ◽  
Author(s):  
Cédric Rebolho ◽  
Vazken Andréassian ◽  
Nicolas Le Moine
Keyword(s):  
Model Performance ◽  
Model Complexity ◽  
Hydraulic Geometry ◽  
Future Event ◽  
New Approach ◽  
Flow Equations ◽  
Geometrical Properties ◽  
Inundation Maps ◽  
Extreme Flood ◽  
Inundation Mapping

Abstract. The production of spatially accurate representations of potential inundation is often limited by the lack of available data as well as model complexity. We present in this paper a new approach for rapid inundation mapping, MHYST, which is well adapted for data-scarce areas; it combines hydraulic geometry concepts for channels and DEM data for floodplains. Its originality lies in the fact that it does not work at the cross section scale but computes effective geometrical properties to describe the reach scale. Combining reach-scale geometrical properties with 1-D steady-state flow equations, MHYST computes a topographically coherent relation between the “height above nearest drainage” and streamflow. This relation can then be used on a past or future event to produce inundation maps. The MHYST approach is tested here on an extreme flood event that occurred in France in May–June 2016. The results indicate that it has a tendency to slightly underestimate inundation extents, although efficiency criteria values are clearly encouraging. The spatial distribution of model performance is discussed and it shows that the model can perform very well on most reaches, but has difficulties modelling the more complex, urbanised reaches. MHYST should not be seen as a rival to detailed inundation studies, but as a first approximation able to rapidly provide inundation maps in data-scarce areas.

A New Deterministic Approach Using Sensitivity Region Measures for Multi-Objective Robust and Feasibility Robust Design Optimization

2005 ◽  
Vol 128 (4) ◽  
pp. 874-883 ◽  
Author(s):  
Mian Li ◽  
Shapour Azarm ◽  
Art Boyars
Keyword(s):  
Pareto Front ◽  
Optimization Problems ◽  
Continuous Functions ◽  
Robust Design Optimization ◽  
Worst Case ◽  
New Approach ◽  
Multi Objective ◽  
Tolerance Region ◽  
Parameter Variations ◽  
Gradient Based

We present a deterministic non-gradient based approach that uses robustness measures in multi-objective optimization problems where uncontrollable parameter variations cause variation in the objective and constraint values. The approach is applicable for cases that have discontinuous objective and constraint functions with respect to uncontrollable parameters, and can be used for objective or feasibility robust optimization, or both together. In our approach, the known parameter tolerance region maps into sensitivity regions in the objective and constraint spaces. The robustness measures are indices calculated, using an optimizer, from the sizes of the acceptable objective and constraint variation regions and from worst-case estimates of the sensitivity regions’ sizes, resulting in an outer-inner structure. Two examples provide comparisons of the new approach with a similar published approach that is applicable only with continuous functions. Both approaches work well with continuous functions. For discontinuous functions the new approach gives solutions near the nominal Pareto front; the earlier approach does not.

A New Approach on Mounting Systems Optimization

2003 ◽  
Author(s):  
Reza Madjlesi ◽  
Amir Khajepour ◽  
Brad Schubert ◽  
Fathy Ismail
Keyword(s):  
Path Analysis ◽  
Optimization Technique ◽  
Optimization Procedure ◽  
System Optimization ◽  
Optimization Method ◽  
Trial And Error ◽  
Target Response ◽  
New Approach ◽  
Weakly Coupled ◽  
Noise Vibration

Vehicles are assemblies of subsystems or modules, which are developed in parallel at multiple locations and often for more than one vehicle. CAE software provides the integration of modules in a complete vehicle in parallel; however the whole system requires final adjustments and tunings. These adjustments, especially in suspensions and mounting systems are very time consuming and are generally based upon trial and error techniques. To reduce the number of trials, usually noise path analysis (NPA) is used. In this technique, the noise and vibration paths for each mount to the objective point are measured. Using the measured data, the dominant path is detected. A highly experienced NVH engineer now can use the information to tune the mount to satisfy the target response. This technique is appropriate if the subsystems are weakly coupled. This situation is not usually the case in engine mounting systems where any modification in one of the mounts may change the dominant path. An important step to reduce refinement time is to develop a method to obtain the overall model of the whole vehicle. In this paper, we introduce a new approach in vehicle’s NVH development. In this approach, the model of the vehicle for mounting system optimization is obtained based on the FRF synthesis. A hybrid analytical/experimental model of the vehicle is developed to predict the NVH response of the vehicle for any given mounting system. This model along with an optimization technique is used to arrive at the optimum mounting system for any objective function. The optimization method is linked with the noise path analysis (NPA), which is used to specify the dominant directions that the noise/vibration is transferred to the response point. These directions are used in the optimization procedure to find the optimum mounting system with minimum calculation time. Experimental results on a full size car are presented to evaluate new approach.

Design of the SAFER Emergency Gate Using LS-DYNA

2005 ◽  
Author(s):  
Robert W. Bielenberg ◽  
John D. Rohde ◽  
John D. Reid
Keyword(s):  
Impact Load ◽  
High Strength ◽  
Full Scale ◽  
Element Analysis ◽  
Worst Case ◽  
Crash Testing ◽  
Additional Protection ◽  
Energy Absorbing ◽  
The Impact ◽  
Gate Design

In recent years, NASCAR and the Indy Racing League have improved the safety of their racetracks through the installation of the Steel And Foam Energy Reduction barrier (SAFER). The new barrier consists of a high-strength, tubular steel skin that distributes the impact load to energy-absorbing foam cartridges in order to reduce the severity of the impact, extends the impact event, and provides the occupant of the race car additional protection. During installation of the SAFER barrier, the designers realized that certain race tracks were designed with the emergency track exit in the outside of the corner. Because the SAFER barrier needed to be installed in these corners, a gate mechanism had to be designed for the barrier that would provide access to the track while retaining the safety performance of the system. Full-scale crash testing of the first SAFER gate design showed that the gate did not posses sufficient capacity to handle the loads experienced during a worst-case impact scenario. Non-linear finite element analysis was then used to redesign the gate mechanism. The original gate design was simulated using LS-DYNA in order to validate the computational model. Modifications to increase the capacity of the gate mechanism were designed and analyzed until suitable results were obtained through simulation. Finally, the redesigned SAFER gate was successfully full-scale crash tested.

scholarly journals Influence Maximization with Priority in Online Social Networks

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 183
Author(s):  
Canh V. Pham ◽  
Dung K. T. Ha ◽  
Quang C. Vu ◽  
Anh N. Su ◽  
Huan X. Hoang
Keyword(s):  
Social Network ◽  
Online Social Networks ◽  
Sampling Method ◽  
State Of The Art ◽  
Influence Maximization ◽  
Approximation Solution ◽  
Worst Case ◽  
New Approach ◽  
Influence Spread ◽  
Seed Collections

The Influence Maximization (IM) problem, which finds a set of k nodes (called seedset) in a social network to initiate the influence spread so that the number of influenced nodes after propagation process is maximized, is an important problem in information propagation and social network analysis. However, previous studies ignored the constraint of priority that led to inefficient seed collections. In some real situations, companies or organizations often prioritize influencing potential users during their influence diffusion campaigns. With a new approach to these existing works, we propose a new problem called Influence Maximization with Priority (IMP) which finds out a set seed of k nodes in a social network to be able to influence the largest number of nodes subject to the influence spread to a specific set of nodes U (called priority set) at least a given threshold T in this paper. We show that the problem is NP-hard under well-known IC model. To find the solution, we propose two efficient algorithms, called Integrated Greedy (IG) and Integrated Greedy Sampling (IGS) with provable theoretical guarantees. IG provides a 1−(1−1k)t-approximation solution with t is an outcome of algorithm and t≥1. The worst-case approximation ratio is obtained when t=1 and it is equal to 1/k. In addition, IGS is an efficient randomized approximation algorithm based on sampling method that provides a 1−(1−1k)t−ϵ-approximation solution with probability at least 1−δ with ϵ>0,δ∈(0,1) as input parameters of the problem. We conduct extensive experiments on various real networks to compare our IGS algorithm to the state-of-the-art algorithms in IM problem. The results indicate that our algorithm provides better solutions interns of influence on the priority sets when approximately give twice to ten times higher than threshold T while running time, memory usage and the influence spread also give considerable results compared to the others.

ORGANIZED SUPERSTRUCTURES AT NANOSCALE AND NEW FUNCTIONAL NANOMATERIALS

2007 ◽  
Vol 06 (05) ◽  
pp. 373-377 ◽  
Author(s):  
V. KISLOV ◽  
B. MEDVEDEV ◽  
YU. GULYAEV ◽  
I. TARANOV ◽  
V. KASHIN ◽  
...  
Keyword(s):  
Electronic Devices ◽  
Self Organization ◽  
Research Groups ◽  
Functional Nanomaterials ◽  
Nano Technology ◽  
New Approach ◽  
Geometrical Properties ◽  
Self Assembling ◽  
Linearly Polarized ◽  
Russian Research

We report on a number of new effects of self-organization at nanoscale, leading to creation of new functional nanomaterials, including carbon and carbon–metal nanotoroids and nanodiscs and self-assembling of magnetic nanoparticles into helices and chains. We also extensively used a new approach of biopattern nanoengineering to create DNA-based complexes with metal or CdSe / ZnS core-shell nanorods (22 × 4.5 nm) which possess strong linearly polarized photoluminescence due to unidirectional orientation of nanorods along DNA filaments. Optical, electrical, and topological (geometrical) properties of such complexes were investigated. This work is a result of a coherent effort (since 1980s) of a consortium of Russian research groups in Nano-technology (INTC: Interdisciplinary Nanotechnology Consortium) aimed at creating molecular electronic devices based on individual and collective properties of specially designed and fabricated nanoclusters.

Modeling the Evolution of Glyphosate Resistance in Barnyardgrass (Echinochloa crus-galli) in Cotton-Based Production Systems of the Midsouthern United States

2013 ◽  
Vol 27 (3) ◽  
pp. 475-487 ◽  
Author(s):  
Muthukumar V. Bagavathiannan ◽  
Jason K. Norsworthy ◽  
Kenneth L. Smith ◽  
Paul Neve
Keyword(s):  
United States ◽  
Weed Management ◽  
Production Systems ◽  
Relative Effectiveness ◽  
Glyphosate Resistance ◽  
Case Scenario ◽  
Management Options ◽  
Worst Case ◽  
Resistance Evolution ◽  
Initial Frequency

Glyphosate-resistant (GR) weeds have been a prime challenge to the sustainability of GR cotton-based production systems of the midsouthern United States. Barnyardgrass is known to be a high-risk species for evolving herbicide resistance, and a simulation model was developed for understanding the likelihood of glyphosate resistance evolution in this species in cotton-based systems. Under a worst-case scenario of five glyphosate applications in monoculture GR cotton, the model predicts resistance evolution in about 9 yr of continuous glyphosate use, with about 47% risk by year 15. A unique insight from this model is that management in response to GR Palmer amaranth in this system (a reactive response) provided a proactive means to greatly reduce the risks of glyphosate resistance evolution in barnyardgrass. Subsequent model analysis revealed that the risk of resistance is high in fields characterized by high barnyardgrass seedbank levels, seedling emergence, and seed production per square meter, whereas the risk is low in fields with high levels of postdispersal seed loss and annual seedbank loss. The initial frequency of resistance alleles was a high determinant of resistance evolution (e.g., 47% risk at year 15 at an initial frequency of 5e−8vs. 4% risk at 5e−10). Monte Carlo simulations were performed to understand the influence of various glyphosate use patterns and production practices in reducing the rate and risk of glyphosate resistance evolution in barnyardgrass. Early planting and interrow cultivation are useful tools. Crop rotation is effective, but the diversity of weed management options practiced in the rotational crop is more important. Diversifying weed management options is the key, yet application timing and the choice of management option is critical. Model analyses illustrate the relative effectiveness of a number of diversified glyphosate use strategies in preventing resistance evolution and preserving the long-term utility of glyphosate in midsouthern U.S. cotton-based production systems.

scholarly journals A New Approach for Detecting and Resolving Anomalies in Security Policy of the External Firewall Module of the Floodlight SDN Controller

2018 ◽  
Vol 25 (3) ◽  
pp. 251-256
Author(s):  
Sergey V. Morzhov ◽  
Mikhail A. Nikitinskiy
Keyword(s):  
Data Structure ◽  
Security Policy ◽  
Stress Testing ◽  
Worst Case ◽  
New Approach ◽  
Filtering Method ◽  
Performance Problem ◽  
Network Application ◽  
Sdn Controller ◽  
Adequate Data

In this paper, the authors analyze the developed PreFirewall network application for the Floodlight software defined network (SDN) controller. This application filters rules, which are added into the firewall module of the Floodlight SDN controller in order to prevent the occurrence of anomalies among them. The rule filtering method is based on determining whether the addition of a new rule will not cause any anomalies with already added ones. If an anomaly was detected while adding the new rule, PreFirewall application should be able to resolve it and must report the detection of the anomaly. The developed network application PreFirewall passed a number of tests. As a result of the stress testing, it was found that the time of adding a new rule, when using PreFirewall, substantially increases with increase in the number of previously processed rules. Analysis of the network application PreFirewall showed that while adding a rule (the most frequent operation), in the worst case it is necessary to compare it with all existing rules, which are stored as a two-dimensional array. Thus, the operation of adding a new rule is the most time-consuming and has the greatest impact on the performance of the network application, which leads to an increase in response time. A possible way to of solving this problem is to select a data structure used to store the rules, in which the operation of adding a new rule would be simple. After analyzing the structure of the policy rules for the Floodlight SDN controller, the authors noted that a tree is the most adequate data structure for its storage. It provides optimization of memory used for storing the rules and, more important, it allows to achieve the constant complexity of the operation of adding a new rule and, consequently, solving the performance problem of the network application PreFirewall. The article is published in the authors’ wording.

scholarly journals An Executive Approach to Achieve Mutual Exclusion in Distributed Data using Topology and Association Rule.

2014 ◽  
Vol 13 (6) ◽  
pp. 4537-4542
Author(s):  
Mr. Anurag Singh ◽  
Dr. Amod Tiwari
Keyword(s):  
Distributed System ◽  
Association Rule ◽  
Message Passing ◽  
Computer Network ◽  
Mutual Exclusion ◽  
Distributed Data ◽  
Worst Case ◽  
New Approach ◽  
And Topology ◽  
Minimum Number

In this paper, a new approach is being proposed to achieve mutual exclusion in distributed system using computer network and topology of nth nodes. In this executive approach nodes communicate among themselves using message passing technique. In this executive approach, distributed system with n nodes is logically partitioned into number of sub distributed system having only m½ nodes, where m is obtained by adding a minimum number in n to make it next perfect square number only if n is not a perfect square. Proposed algorithm is a Token based approach and achieves token optimally in 2 messages only for the best case and in worst case a node achieves token in n messages only.

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