Dynamic Program Analysis Research Articles

Stability Evaluation of the Transmission Line by using Galloping Simulation

Galloping phenomenon is one of the vibrations caused by icing. If galloping phenomenon continues, short-circuit or ground fault may occur, so analysis of galloping phenomenon through research on transmission line stability is necessary. The DenHartog method, which is frequently used for the galloping stability determination of the transmission line, considers only the vertical movement of the transmission line. In this study, we analyze the motion of multi-degree-of-freedom objects, using a computer aided engineering program. We modeled transmission lines as a multi mass-spring-damper systems using RecurDyn, which is a multibody commercial dynamics analysis program to analyze the galloping phenomenon dynamically. Damping inside transmission line derived from the Rayleigh damping theory through the free vibration experiment of transmission line. ANSYS Fluent, a flow analysis program, was used to derive the aerodynamic coefficients for transmission line with asymmetric cross-section. Using the derived aerodynamic coefficient, we confirmed the galloping occurrence condition of DenHartog method and modeled the wind load acting on the transmission line to conduct galloping simulation. Through the analysis of the motion of a multi-degree-of-freedom transmission line, the occurrence of galloping was classified into ovoid and vertical trajectories, and the case of no galloping was defined as regular trajectory, and the range of angle of attack that causes the instability of transmission lines was defined.

Reduction of flow-induced noise in a household air purifier

In this study, we propose a design for a household air purifier that reduces the flow-induced noise caused by the impeller of the fan system. The noise of the air purifier was identified in experiments as induced by the air flow generated by the impeller of the purifier. This noise can be classified into tonal noise and wide-band frequency noise: The former is the noise from the impeller blade turning, and the latter is from air flow turbulence. Using a commercial computational fluid dynamics (CFD) analysis code, it was shown that flow separation occurs at the outlet of the scroll by the adverse pressure gradient, which significantly reduces the flow rate of the purifier. To avoid flow separation and maximize flow rate within the adjustable ranges of the design parameters, an improved air purifier was redesigned using an orthogonal array table. By CFD analysis, the improved design showed an increased flow rate without flow separation. Finally, after fabricating a prototype with the improved design, it was experimentally proven that noise was reduced by 4.2 dBA without sacrificing flow rate.

Critical Velocity of Short Floating Slab Track Using Alterable Element Method Considering Wheel-Rail Contact Loss

In actual line operation, the critical velocity is one of the key physical quantities of rail design owing to its great influence on the riding comfort and safety of vehicles due to the wheel-rail contact loss caused by the abrupt change of rail foundation rigidity, rail wear, or abruptness irregularities on rail. In this study, the short floating slab track (SFST) structure is regarded as a double-layer system. The Euler beam and the rigid body model are adopted for the rail and the floating slab, respectively, and the dispersion equation and the theoretical critical velocity of the rail structure under ideal conditions are deduced. Besides, this study considers the implementation of the SFST in the vehicle-structure coupling system. The alterable element method is introduced for accurately simulating the change of the wheel-rail contact state and coding a vehicle-structure dynamic analysis program (VSDAP) to calculate the critical velocity of rail structures from the dynamic response of vehicles and rail structures. The principle of its design at the beginning of the design is given on the basis of the theoretical value of the critical velocity and the simulation of the dynamic response, which can provide reference for practical engineering design.

Developing Consumer Electronics Software Using A-SPICE: Infotainment Development Experience

This article presents one experience with the design and implementation of a consumer electronics (CE) software module using automotive software process improvement and capability determination (A-SPICE) methodology. Electronic program guide (EPG) engine software module is a very stable, configurable product that ensures high performance and satisfies different television standards. It is designed to operate on a wide range of hardware platforms, especially in automotive multimedia systems. Since the EPG engine had to be integrated into the automotive infotainment system, that module was developed in compliance with the Hersteller Initiative Software-Manufacturer's software initiative metrics and A-SPICE standard. Application lifecycle management tool was used in the development process for project management and for generating data for analysis purposes. The software itself was tested during the whole project lifecycle using several static and dynamic code analysis methods. Difficulties concerning testing procedures, code quality, and complying with A-SPICE standard were detected and resolved. Since the CEs software development is not that strict as automotive one, this article points out the advantages of introducing the A-SPICE methodology in the CE field.

Vibration Soil Crushing Mechanism of Self-excited Vibration Subsoiler in Coastal Area

Ma, X.; Wang, S., and Wang, H., 2020. Vibration soil crushing mechanism of self-excited vibration subsoiler in coastal area. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 426–430. Coconut Creek (Florida), ISSN 0749-0208.According to the characteristics of high alkalinity and humidity in the coastal area, the self-excited vibration subsoiler is designed, and the subsoiling mechanism is designed as layered structure. The LS-DYNA explicit dynamics analysis program was used to simulate the working process of non-vibration and vibration subsoiling respectively. In the process of subsoiling, the action process of two kinds of subsoiling mechanism on soil, the stress change of subsoiling mechanism and soil respectively, and the mechanism of soil crushing of soil vibration are studied. It can be seen from the analysis that under the condition of vibration, the resistance of the soil to the subsoil shovel is reduced, the shear force of the subsoil shovel to the soil is increased. The soil debris is more uniform, there is no fracture phenomenon in the upper and lower layers of soil, and the subsoil effect is better.

A novel power management strategy for hybrid off-road vehicles

Hybrid off-road vehicles generally use an engine and an energy storage system (e.g., ultracapacitor) as the power sources for propulsion. By optimally splitting power demand to different actuators (i.e., electric motors), fuel economy can be improved greatly. Thus, the control strategies of hybrid vehicles play an important role in fuel savings. While many optimal control strategies have been proposed, two major concerns present themselves: the need for prior knowledge of future driving conditions and the slow computation speed. In this paper, a novel near-optimal power management strategy, called efficiency-based evaluation real time control strategy (EERCS), is developed to rapidly obtain near-optimal fuel economy. We formulate the normalized efficiency of power flow as the criterion. By maintaining high system efficiency under all conditions, the controller can obtain near-optimal fuel economy with no need for prior knowledge. To validate the control effect, the proposed novel controller is compared with dynamic programming (DP) and power-weighted efficiency analysis for rapid sizing (PEARS+). A complex multi-mode power-split hybrid track-type dozer is selected for the case study. Simulation results show that the new power management strategy produces results similar to those of DP and PEARS+ together, with a faster computation speed. Two distributed drive cycles are used to verify the robustness of EERCS. The resulting control law can also be applied online as a static mapping function of the powertrain state. The proposed novel strategy is also a promising control tool that can be extended to other types of hybrid electric vehicles.

Recommending refactorings via commit message analysis

Abstract Context The purpose of software restructuring, or refactoring, is to improve software quality and developer productivity. Objective Prior studies have relied mainly on static and dynamic analysis of code to detect and recommend refactoring opportunities, such as code smells. Once identified, these smells are fixed by applying refactorings which then improve a set of quality metrics. While this approach has value and has shown promising results, many detected refactoring opportunities may not be related to a developer’s current context and intention. Recent studies have shown that while developers document their refactoring intentions, they may miss relevant refactorings aligned with their rationale. Method In this paper, we first identify refactoring opportunities by analyzing developer commit messages and check the quality improvements in the changed files, then we distill this knowledge into usable context-driven refactoring recommendations to complement static and dynamic analysis of code. Results The evaluation of our approach, based on six open source projects, shows that we outperform prior studies that apply refactorings based on static and dynamic analysis of code alone. Conclusion This study provides compelling evidence of the value of using the information contained in existing commit messages to recommend future refactorings.

Practical Approach for Developing Lateral Motion Control of Autonomous Lane Change System

In this paper, we present a practical approach to address the vehicle lateral control problem. The proposed method can overcome practical problems associated with vehicle lane changes on highways. The vehicle state with respect to the road, which is called lateral offset, jumps in camera vision sensors when the vehicle changes lanes. Thus, in this study, we solve the state jump problem by translating it into a new domain called the cylinder domain. In addition, we proposed the design of a parameter-varying controller to overcome the nonlinear term of vehicle dynamics by considering it as a varying parameter. The proposed method does not consider the lateral offset jump when changing lanes. Furthermore, its significant advantage in terms of computation time makes it suitable for implementation in low-cost electronic control units (ECUs). The proposed algorithm is validated using MATLAB/Simulink with the vehicle dynamics analysis program CarSim.

Bovine mastitis and optimal disease management: Dynamic programming analysis

Wise decision-making for coping with infectious diseases is a key to the success of farming, agriculture, as well as public health. Mastitis of dairy cows causes large economic burden to dairy farmers. Here, we study the optimal operation for a dairy farmer to manage cows infected by mastitis. In the simple model, we considered cows with different number of breasts (quarters) infected by mastitis. In the detailed model, we considered additional complexities: a cow produces milk only after the first birth of a calf, old cows are culled, milking is not practiced for 10 weeks prior to expected calf-birth, and a newborn calf provides an economic benefit. By fitting the parameters to the Japanese dairy farming situation, the dynamic programming analysis reveals whether an infected cow should receive medical treatment depends on the number of breasts infected, age, and season. Cows should be culled if many breasts are infected, they are old, and it is not close to the next calf-birth. The optimal management policy depends critically on milk price, maintenance cost, and recovery rate from mastitis infection, but not on infection rate.

Dynamic response of saddle membrane structure under hail impact

In this paper, the dynamic response of a typical four-point pretensioned saddle membrane structure under hail impact load is investigated by numerical simulations and experimental studies. Firstly, the initial shape of saddle membrane is obtained by form-finding analysis using the finite element analysis software ANSYS. The complex mechanical process of hail impact on the flexible membrane is simulated by LS-DYNA/Explicit dynamic analysis program, and the dynamic response of membrane, including displacement, velocity and acceleration, etc, is characterized. Then the experiment of saddle membrane under hail impact is carried out by applying the same loading conditions with the numerical analysis. The comparison between the numerical and experimental results shows good agreement, which verifies the reliability of the numerical simulations. It is discovered that the pretension relaxation induced by the hail impact may decrease the critical wind speed of membrane, and significantly increase the risk of membrane instability subject to hailstorm. Finally, the dynamic characteristics of typical four-point tensioned saddle membrane are summarized, which may provide reference for the design, construction and maintenance of membrane structures.

An analysis of risk aversion in biotechnology adoption: the case of US genetically modified corn

This paper analyzes the role of risk aversion in biotechnology adoption with the application on the US genetically modified corn. A dynamic programming analysis of technology adoption is conducted using the Kalman filter as a representation of the associated learning process. The relevant Bellman equation is jointly solved within model estimation using a minimum-distance estimator. Results show that the more the risk-averse farmers are, the later they adopt GM technology, such effects being statistically significant. Sensitivity analysis results examine the factors affecting farmers’ behavior. They document the role of risk aversion in technology adoption. They also uncover the presence of farm heterogeneity in the process of adopting a new technology.

A study of run-time behavioral evolution of benign versus malicious apps in android

Abstract Context The constant evolution of the Android platform and its applications have imposed significant challenges both to understanding and securing the Android ecosystem. Yet, despite the growing body of relevant research, it remains unclear how Android apps evolve in terms of their run-time behaviors in ways that impede our gaining consistent empirical knowledge about the workings of the ecosystem and developing effective technical solutions to defending it against security threats. Intuitively, an essential step towards addressing these challenges is to first understand the evolution itself. Among others, one avenue to examining a program’s run-time behavior is to dissect the program’s execution in terms of its syntactic and semantic structure. Objective In this paper, we study how benign Android apps execute differently from malware over time, in terms of their execution structures measured by the distribution and interaction among functionality scopes, app components, and callbacks. In doing so, we attempt to reveal how relevant app execution structure is to app security orientation (i.e., benign or malicious). Method By tracing the method calls and inter-component communications (ICCs) of 15,451 benign apps and 15,183 malware developed during eight years (2010–2017), we systematically characterized the execution structure of malware versus benign apps and revealed similarities and disparities between them that are not previously known. Results Our results show, among other findings, that (1) despite their similarity in execution distribution over functionality scopes, malware accessed framework functionalities mainly through third-party libraries, while benign apps were dominated by calls within the framework; (2) use of Activity component had been rising in malware while benign apps saw continuous drop in such uses; (3) malware invoked significantly more Services but less Content Providers than benign apps during the evolution of both groups; (4) malware carried ICC data significantly less often via standard data fields than benign apps, albeit both groups did not carry any data in most ICCs; and (5) newer malware tended to have more even distribution of callbacks among event-handler categories, while the distribution remained constant in benign apps over time. Conclusion We discussed how these findings inform understanding app behaviors, optimizing static and dynamic code analysis of Android apps, and developing sustainable app security defense solutions.

Post-blast performance and residual capacity of CFDST columns subjected to contact explosions

Contact detonations, even with a small charge weight, could cause severe damage to structural columns and result in devastating consequences, associate with significant casualties, economic losses and social impacts. Therefore, to prevent catastrophic structural collapse, the most critical requirement of a blast-damaged column would be the residual axial load bearing capacity. In this paper, the post-blast performance of concrete-filled double-skin steel tube (CFDST) columns subjected to contact explosions was studied by experimental tests and numerical simulations. The experimental study comprised of field blast tests and residual axial load-carrying capacity tests on four CFDST columns. A high-fidelity physics-based numerical model was then developed using the nonlinear dynamic analysis program LS-DYNA and was validated against the test results. It was then used to model the dynamic response and predict the residual axial load-carrying capacity of CFDST columns subjected to contact explosions. An extensive parametric study was then carried out to investigate the influence of charge weight, boundary conditions, axial loading level and column geometries on the column residual axial load-carrying capacity. An empirical formula was derived through multi-variable regression analysis to predict the residual axial bearing capacity of CFDST columns after contact explosions.

Numerical simulation of directional fracturing by shaped charge blasting

AbstractThe hard roof leads to large deformation or failure of the entry and poses risks to mining safety. Shaped charge blasting is applied to directionally fracture the hard roof and release mining pressure in this paper. The stress condition around the blasting borehole required to induce fracture propagation is calculated by theoretical calculation and numerical simulation. Evolution of blasting‐induced fractures between adjacent boreholes, main fracture in the shaped charge jet direction and secondary fractures in other directions is analyzed. The reliability of Livemore software of explicit dynamics analysis code (LS‐DYNA) in simulating shaped charge blasting is validated by experimental results. A numerical model is established to reveal the formation processes of the shaped charge jet, disclose the evolution of the equivalent stress and understand the development of the main fractures and secondary fractures between adjacent boreholes. The failure type of the rock mass and the fracture development zone are identified. The results indicate that blasting‐induced fractures mainly initiate and propagate in the shaped charge jet direction between adjacent boreholes. Shaped charge blasting leads to the directional propagation of fractures. The field monitoring results show that shaped charge blasting is able to realize the directional propagation of blasting‐induced fractures and release mining pressure.

Increasing the reliability of information management systems for complex objects

This article describes one of the possible approaches to the implementation of a set of mechanisms and tools for assessing and monitoring software safety based on static and dynamic analysis of programs, which provides an effective check of the operating and developed software. To solve this problem, it is proposed to use mathematical models of program circuits, modern software development technologies and methods of software analysis.

A Comparative Study of Static Code Analysis tools for Vulnerability Detection in C/C++ and JAVA Source Code

Abstract Software security has become an essential component of software development process. It is necessary for an organisation to maintain software security in order to ensure integrity, authenticity and availability of the software product. To ensure software security, one of the major task is to identify vulnerabilities present in the source code before the software is being deployed. Detecting vulnerabilities in early phases of software development cycle, makes the process of fixing those vulnerabilities much easier for software developers. The vulnerability detection can be done either at the production phase, this means when the software is still being developed by statically auditing the source code, or dynamically at run time. In this study, vulnerability detection was done through Static code analysis process. Static code analysis can be done either manually or through automated tools. This paper focuses on using automated source code scanning tools for vulnerabilities detection in a software. Automated static Code Analysis tools audits the entire source code for its quality and identify any potential security vulnerability, if present. Unlike dynamic source code analysis that evaluates the source code behaviour during code execution, which is done quite late in the software development life cycle, Static Code Analysis leads to detection of security vulnerabilities in a source code in early stages of software development process, when the software is still in production phase because it does not require code to be in execution state. This paper firstly explains the importance of incorporating static code analysis in software development life cycle process so as to facilitate early detection of vulnerabilities in software product, and then present a comparative study of various static code analysis tools available for vulnerability detection in C/C++ and JAVA source code. The comparative study of three C/C++ static code analysis tools (flawfinder, RATS and CPPCheck) and two JAVA static code analysis tools (spotbugs and PMD) is done using Juliet (version1.3) test suite and APACHE tomcat dataset respectively, on the basis of category of vulnerability detected by each of the selected tool and the likelihood of false positive reported by each tool. Results showed that Flawfinder detected maximum categories of vulnerabilities and RATS and CPPCheck were almost similar in types of vulnerabilities detected. Also, it was observed that CPPCheck reported maximum number of false positives as compared to other two tools. Java static code analysis tools Spot bugs was able to detect more number of vulnerabilities than PMD.

Dynamic programming and feedback analysis of the two dimensional tidal dynamics system

In this work, we consider the controlled two dimensional tidal dynamics equations in bounded domains. A distributed optimal control problem is formulated as the minimization of a suitable cost functional subject to the controlled 2D tidal dynamics equations. The existence of an optimal control is shown and the dynamic programming method for the optimal control of 2D tidal dynamics system is also described. We show that the feedback control can be obtained from the solution of an infinite dimensional Hamilton-Jacobi equation. The non-differentiability and lack of smoothness of the value function forced us to use the method of viscosity solutions to obtain a solution of the infinite dimensional Hamilton-Jacobi equation. The Bellman principle of optimality for the value function is also obtained. We show that a viscosity solution to the Hamilton-Jacobi equation can be used to derive the Pontryagin maximum principle, which give us the first order necessary conditions of optimality. Finally, we characterize the optimal control using the adjoint variable.

Parallelization of Implementations of Purely Sequential Algorithms

The work is dedicated to the parallelization of programs in especially difficult cases when the used algorithm is purely sequential, there are no parallel alternatives to this algorithm, and its execution time is unacceptably high. Various parallelization methods for software implementations of such algorithms and resulting computational load balancing are considered that make it possible to considerably accelerate the execution of application programs using purely sequential algorithms. The proposed methods are illustrated with examples of their application to two algorithms used in a dynamic binary code analysis toolset. The main goal of this paper is to show that the use of a purely sequential algorithm in a software implementation does not necessarily imply that its execution is inevitably sequential. The proposed methods of parallelizing implementations of such algorithms and balancing the resulting computational load can help develop efficient parallel programs that fully utilize the hardware capabilities of modern computers.

Diffusion Approximations for a Class of Sequential Testing Problems

We consider a decision maker who must choose an action in order to maximize a reward function that depends on the action that she selects as well as on an unknown parameter “Theta”. The decision maker can delay taking the action in order to experiment and gather additional information on “Theta”. We model the decision maker's problem using a Bayesian sequential experimentation framework and use dynamic programming and diffusion-asymptotic analysis to solve it. For that, we scale our problem in a way that both the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regime, we derive a diffusion approximation for the sequential experimentation problem, which provides a number of important insights about the nature of the problem and its solution. First, it reveals that the problems of (i) selecting the optimal sequence of experiments to use and (ii) deciding the optimal time when to stop experimenting decouple and can be solved independently. Second, it shows that an optimal experimentation policy is one that chooses the experiment that maximizes the instantaneous volatility of the belief process. Third, the diffusion approximation provides a more mathematically malleable formulation that we can solve in closed form and suggests efficient heuristics for the non-asympototic regime. Our solution method also shows that the complexity of the problem grows only quadratically with the cardinality of the set of actions from which the decision maker can choose. We illustrate our methodology and results using a concrete application in the context of assortment selection and new product introduction. Specifically, we study the problem of a seller who wants to select an optimal assortment of products to launch into the marketplace and is uncertain about consumers' preferences. Motivated by emerging practices in e-commerce, we assume that the seller is able to use a {\em crowdvoting} system to learn these preferences before a final assortment decision is made. In this context, we undertake an extensive numerical analysis to assess the value of learning and demonstrate the effectiveness and robustness of the heuristics derived from the diffusion approximation.

동적 코드 분석을 위한 전처리부 설계 및 구현

최근 다양한 형태의 악성코드 등장으로 인해 기존의 정적 분석은 많은 한계를 노출하고 있다. 정적분석 은 (악성)코드를 실제로 실행하지 않고 원시 코드나 목적 코드를 가지고 코드나 프로그램의 구조를 분석 하는 것을 의미한다. 한편 정보보안 분야에서의 동적 분석이란 일반적으로 (악성)코드를 직접 실행하여 분석하는 형태로 프로그램의 실행 플로우를 파악하기 위해 (악성)코드의 실행 전후 상태를 비교·조사하여 분석하는 형태를 의미한다. 그러나 동적 분석을 위해서는 막대한 양의 데이터와 로그를 분석해야 하며 모 든 실행 플로우를 실제로 저장하기도 어려웠다. 본 논문에서는 윈도우 환경(윈도우 10 R5 이상)에서 2세 대 PT를 기반으로 악성코드 탐지 및 실시간 다중 동적 분석을 수행하는 시스템의 전처리기 구조를 제안 하였고 이를 구현하였다.