Development of an object-oriented finite element program: application to metal-forming and impact simulations

During the last 50 years, the development of better numerical methods and more powerful computers has been a major enterprise for the scientific community. In the same time, the finite element method has become a widely used tool for researchers and engineers. Recent advances in computational software have made possible to solve more physical and complex problems such as coupled problems, nonlinearities, high strain and high-strain rate problems. In this field, an accurate analysis of large deformation inelastic problems occurring in metal-forming or impact simulations is extremely important as a consequence of high amount of plastic flow. In this presentation, the object-oriented implementation, using the C++ language, of an explicit finite element code called DynELA is presented. The object-oriented programming (OOP) leads to better-structured codes for the finite element method and facilitates the development, the maintainability and the expandability of such codes. The most significant advantage of OOP is in the modeling of complex physical systems such as deformation processing where the overall complex problem is partitioned in individual sub-problems based on physical, mathematical or geometric reasoning. We first focus on the advantages of OOP for the development of scientific programs. Specific aspects of OOP, such as the inheritance mechanism, the operators overload procedure or the use of template classes are detailed. Then we present the approach used for the development of our finite element code through the presentation of the kinematics, conservative and constitutive laws and their respective implementation in C++. Finally, the efficiency and accuracy of our finite element program are investigated using a number of benchmark tests relative to metal forming and impact simulations

The Improvement of Efficiency in the Numerical Computation of Orbit Trajectories

An analysis, system design, programming, and evaluation of results are described for numerical computation of orbit trajectories. Evaluation of generalized methods, interaction of different formulations for satellite motion, transformation of equations of motion and integrator loads, and development of efficient integrators are also considered

Calculating Corporate Compliance & The Foreign Corrupt Practices Act

Technology is rapidly disrupting every industry and institution around the globe. Yet, corporate compliance has remained relatively unaffected by technological change when compared to other industries. If firms continue to lag behind in their compliance efforts, their risk exposure to the potentially lethal sanctions associated with major compliance failures will continue to increase with time. This is particularly true in the context of the Foreign Corrupt Practices Act. Generally, the Foreign Corrupt Practices Act (“FCPA”) is a regulatory statute that forbids bribery and false accounting for domestic firms doing business abroad. And, in the past decade the DOJ and SEC have begun aggressively enforcing the FCPA. Firms should begin using technology to develop more robust and cost-efficient compliance programs to insulate themselves from the FCPA’s harsh penalties. This Article provides an algorithm that allows firms to evaluate and improve their compliance programs in accordance with several published sources of guidance. Compliance scholars have made clear that it is critical for firms to maintain strong corporate compliance programs and have suggested different models and frameworks for internal evaluation and auditing. However, those suggestions fail to consider how technology may be used to improve the cost-efficiency of corporate compliance and ethics programs. This Article takes an informatics-based approach to evaluating and improving firm compliance by focusing on the most important compliance functions according to the Department of Justice (“DOJ”), courts, and other Government actors. Indeed, firms may drastically improve the cost-efficiency of their compliance efforts by adopting the analytical framework proposed in this Article

Quantum Machine Learning: A Patent Review

One of the central problems bottlenecking machine learning research is classical computational power limits. Quantum computing provides a solution, offering more processing power for less electric cost. Quantum Machine Learning (QML) is a research field at the intersection of quantum computing and machine learning technologies, driving the cutting edge in technological innovation. While the legal literature on software patents is rapidly scaling, the research focused on QML patents is noticeably nascent. As such, this Article contributes the first empirical patent survey for QML technologies

AI Patents: A Data Driven Approach

While artificial intelligence (AI) research brings challenges, the resulting systems are no accident. In fact, academics, researchers, and industry professionals have been developing AI systems since the early 1900s. AI is a field uniquely positioned at the intersection of several scientific disciplines including computer science, applied mathematics, and neuroscience. The AI design process is meticulous, deliberate, and time-consuming – involving intensive mathematical theory, data processing, and computer programming. All the while, AI’s economic value is accelerating. As such, protecting the intellectual property (IP) springing from this work is a keystone for technology firms acting in competitive markets