A phased approach to enable hybrid simulation of complex structures

Hybrid simulation has been shown to be a cost-effective approach for assessing the seismic performance of structures. In hybrid simulation,critical parts of a structure are physically tested,while the remaining portions of the system are concurrently simulated computationally,typically using a finite element model. This combination is realized through a numerical time-integration scheme,which allows for investigation of full system-level responses of a structure in a cost-effective manner. However,conducting hybrid simulation of complex structures within large-scale testing facilities presents significant challenges. For example,the chosen modeling scheme may create numerical inaccuracies or even result in unstable simulations; the displacement and force capacity of the experimental system can be exceeded; and a hybrid test may be terminated due to poor communication between modules(e.g.,loading controllers,data acquisition systems,simulation coordinator). These problems can cause the simulation to stop suddenly,and in some cases can even result in damage to the experimental specimens; the end result can be failure of the entire experiment. This study proposes a phased approach to hybrid simulation that can validate all of the hybrid simulation components and ensure the integrity largescale hybrid simulation. In this approach,a series of hybrid simulations employing numerical components and small-scale experimental components are examined to establish this preparedness for the large-scale experiment. This validation program is incorporated into an existing,mature hybrid simulation framework,which is currently utilized in the Multi-Axial Full-Scale Sub-Structuring Testing and Simulation(MUST-SIM) facility of the George E. Brown Network for Earthquake Engineering Simulation(NEES) equipment site at the University of Illinois at Urbana-Champaign. A hybrid simulation of a four-span curved bridge is presented as an example,in which three piers are experimentally controlled in a total of 18 degrees of freedom(DOFs). This simulation illustrates the effectiveness of the phased approach presented in this paper.

A high-order target phase approach for the station-keeping of periodic orbits

A novel high-order target phase approach(TPhA)for the station-keeping of periodic orbits is proposed in this work.The key elements of the TPhA method,the phase-angle Poincare map and high-order maneuver map,are constructed using differential algebra(DA)techniques to determine station-keeping epochs and calculate correction maneuvers.A stochastic optimization framework tailored for the TPhA-based station-keeping process is leveraged to search for fuel-optimal and error-robust TPhA parameters.Quasi-satellite orbits(QSOs)around Phobos are investigated to demonstrate the efficacy of TPhA in mutli-fidelity dynamical models.Monte Carlo simulations demonstrated that the baseline QSO of JAXA’s Martian Moons eXploration(MMX)mission could be maintained with a monthly maneuver budget of approximately 1 m/s.

Breed and adaptive response modulate bovine peripheral blood cells＇ transcriptome

Background： Adaptive response includes a variety of physiological modifications to face changes in external or internal conditions and adapt to a new situation. The acute phase proteins（APPs） are reactants synthesized against environmental stimuli like stress, infection, inflammation.Methods： To delineate the differences in molecular constituents of adaptive response to the environment we performed the whole-blood transcriptome analysis in Italian Holstein（IH） and Italian Simmental（IS） breeds. For this, 663 IH and IS cows from six commercial farms were clustered according to the blood level of APPs. Ten extreme individuals（five APP＋ and APP-variants） from each farm were selected for the RNA-seq using the Illumina sequencing technology. Differentially expressed（DE） genes were analyzed using dynamic impact approach（DIA）and DAVID annotation clustering. Milk production data were statistically elaborated to assess the association of APP＋ and APP-gene expression patterns with variations in milk parameters.Results： The overall de novo assembly of cDNA sequence data generated 13,665 genes expressed in bovine blood cells. Comparative genomic analysis revealed 1,152 DE genes in the comparison of all APP＋ vs. all APP-variants; 531 and 217 DE genes specific for IH and IS comparison respectively. In all comparisons overexpressed genes were more represented than underexpressed ones. DAVID analysis revealed 369 DE genes across breeds, 173 and 73 DE genes in IH and IS comparison respectively. Among the most impacted pathways for both breeds were vitamin B6 metabolism, folate biosynthesis, nitrogen metabolism and linoleic acid metabolism.Conclusions： Both DIA and DAVID approaches produced a high number of significantly impacted genes and pathways with a narrow connection to adaptive response in cows with high level of blood APPs. A similar variation in gene expression and impacted pathways between APP＋ and APP-variants was found between two studied breeds. Such similarity was also confirmed by annotation clustering of the DE genes. However, IH breed showed higher and more differentiated impacts compared to IS breed and such particular features in the IH adaptive response could be explained by its higher metabolic activity. Variations of milk production data were significantly associated with APP＋ and APP-gene expression patterns.

Implementation Details for the Phase Field Approaches to Fracture

Phase field description of fracture is a very promising approach for simulating crack initiation, propagation, merging and branching. This method greatly reduces the implementation complexity, compared with discrete descriptions of cracks. In this work, we provide an overview of phase field models for quasistatic and dynamic cases. Afterward, we present useful vectors and matrices for the implementation of this method in two and three dimensions.

A Powerful Simulation Language for Large and Complex Models

To tackle large and complex problems, a modern simulation modeling system must posses six characteristics: simplicity, user extensibility, object orientation, flexibility, capability, and initialization. Simplicity allows those users who are nonprofessionals in simulation modeling to use the system to build their models. User extensibility is a self perfection mechanism by which the user is able to extend the abilities of the system for large and complex problems. Object oriented methodology is a natural way of simulation modeling. Flexibility can increase the range to which the system can be applied. Powerful systems satisfy demand for ever growing complicated problems. Efficient facilities for the initialization of a model reduces the pain of initializing complicated models. The GPMS language owns each of these features. It is an English like user extensible simulation language, providing simplicity for less experienced users and allowing new data types to be defined to increase its ability. It gives the user a choice between object oriented and function oriented modeling style. Its flexibility in building models prevents the user from obeying strict rules. Its powerful constructs allow the user to describe arbitrarily complicated models. Intelligent model initialization reduces the user’s effort greatly.

A Discrete Event Simulation Support System in C^(++)

This paper describes a discrete simulation support system that forms major parts of most simulation program. The support system contains three main features which differ from the most of other simulation support systems. It follows a strict three phase structure; supports visual interactive simulation. The principles of designing and implementing of the system are explained module by module.