Computational predictions of complex property trajectories in compositionally graded alloys

The development of sensor technology and deep learning has significantly improved the reliability and practicality of automatic driving technology. In an autonomous driving system, agent trajectory prediction is a complex challenge, which includes the understanding of different and unpredictable behavior patterns of various entities, including vehicles, pedestrians, and other traffic participants, among the data collected by sensors. In this paper, we deeply study two kinds of problems: Single-Agent Trajectory Prediction (SATP) and Multi-Agent Trajectory Prediction (MATP). We propose an innovative model, which combines the attention mechanism and integrates the Liquid Time-Constant (LTC) network with spatio-temporal features and the Mixture of Experts (MoE) framework, termed the Atten-LTC-MoE model. The model is general and extensible to support SATP and MATP problems in different autonomous driving environments. In order to improve computational efficiency and prediction accuracy, lane and agent vectorization, spatio-temporal features, agent data fusion, and trajectory endpoint generation technologies are studied. The effectiveness of our method is verified by comprehensive experiments on Argoverse and Interaction datasets. Our proposed model has been superior to the state-of-the-art models in terms of minADE6 and minFDE6 metrics and has shown significant advantages in the accuracy of agent trajectory prediction and computational performance.

Steady-state numerical solutions of the Euler equations for the flow field about a wing/pylon/finned store configuration at a Mach number of 0.95 have been obtained for several store locations and attitudes. The objectives of the study were to gain insight into requirements for future computational trajectory prediction methods, to compare computationally predicted loads and pressures to measured data, and to investigate a mutual interference correction to a semi-empirical load prediction method. To meet these objectives, computational fluid dynamics (CFD) solutions were used to predict loads with the store placed at its carriage position and at 0.25, 0.50, 1 .O, and 4.0 store body diameters below the carriage position. An additional solution was obtained with the store in a position determined by a wind tunnel trajectory simulation test. Load predictions were also obtained using the Influence Function Method (IFM) for these positions. The CFD-predicted pressure distributions for the store at the carriage and trajectory positions agreed well with the measured test data, and the CFD-predicted loads on the store in these two cases agreed fairly well with the test loads. Conversely, the loads predicted by the basic IFM were in poor agreement for all cases with the measured loads and loads predicted by the CFD calculations. However, when properly applied to the IFM, the mutual interference loads correction provided a reasonable approximation to the CFD-predicted loads. Over the course of this investigation, it was found that grid density, geometric accuracy, and viscosity requirements for CFD trajectory predictions are extremely dependent on the physical properties of the store of interest, the method of release, and the portion of the trajectory over which the calculations will be performed. Nomenclature Influence coefficients used by the Influence Function Method to calculate normal and side forces. Influence coefficients used by the Influence Function Method to calculate yawingand pitching-moment coefficients. Rolling-moment coefficient, (rolling moment)/(Q*SD). Positive in the positive @ sense (see Fig. 1 ). Pitching-moment coefficient taken about the c.g., (pitching moment)/(Q*S*D). Positive in the positive 8 sense (see Fig.1). Normal-force coefficient, (normal force)/ (QnS). Positive in the positive Z direction (see Fig. 1 ). Yawing-moment coefficient taken about the c.g., (yawing moment)/(Q*S*D). Positive in the positive 6 sense (see Fig. 1). Pressure coefficient. Side force coefficient, (side force)/(Q*S). Positive in the positive Y direction (see Fig. 1). Local chord of fin on model store. Store center of gravity located 2.79 in. (model scale) axially from the store nose. Store model diameter, 1 .O .in. Distance over which the double delta correction is applied to the IFM-predicted loads, store diameters. Store model length, 5.941 in. Free-stream Mach number. Free-stream dynamic pressure, 1/2pV2. T h e research reported herem was performed by the Arnold Engineering Development Center (AEDC), A r Force Systems Command Work and analysis for thts research were done by personnel of Calspan Corportat~onJAEDC Operations, operatmg contractor for the AEDC aerospace fl~ght dynam~cs fac l~t~es Further reproduction 1s author~zed to satlsfy needs of the U S Government

Computational fluid dynamics can be a useful tool to explore the store separation event. However, for complex, dynamic configurations the turn-around time and computational requirements for a trajectory prediction can be large. This paper documents work which was performed at the Arnold Engineering Development Center, or AEDC, in an effort to determine practical ways to reduce this solution time without sacrificing solution accuracy. The methods described herein are referred to as approximate methods, since they represent engineering approximations made in the application of the flow solver and associated codes rather than advancements made in the solution algorithm.

Positive and effective management of icebergs around drill rigs on the Canadian East Coast is limited by deficiencies in iceberg handling icebergs roll under tow. Anchor handling tugsare delayed by three to six hours while redeploying towing gear. The troublesome bergs are normally in the range of 50-500,000 tons. Conventional floating polypropylene towing hawsers compound latent instabilities by applying a torque component (other netlike towing geometries control roll for only smaller bergs but tangle during deployment and recovery). Field iceberg survey data was collected and on the basis of Lagragian computer analysis a large sample of simulated bergs were towed from random stable floating positions. Through these energy formulations the maximum "critical" tow force (before roll) was computed and the results showed:Calculated critical forces agreed with apparent bollard pull normally causing roll.Critical force varied widely for a specific berg depending upon tow bearing.Critical forces change completely when the iceberg settles to a new attitude.Iceberg drafts vary as much as 25% depending upon attitude. This paper presents:The results on instrumenting iceberg tow forces on the Aquitaine site during the 1980 drilling program,An operational procedure for predicting critical tow forces on the basis of pre-tow surveys. Introduction Canadian East Coast drilling is limited to as few as 60 days per year by ice conditions. Only after pack ice clears in July does the short 60-120 day operating window open for offshore drilling. In the most northerly active acreage Aquitaine et al. are drilling in 1200 feet at the Hekja site in the Davis Strait with the Ben Ocean Lancer1 In preparation for testing Hekja, improvements in equipment and procedures in 1980 enhanced environmental control in these areas:telemetering current data to predict and compensate for the onset of up to two knots current,automated iceberg plotting and trajectory predictions,computer prediction of maximum allowable bollard tow force for iceberg towing with,tensiometer monitoring of actual bollard pull. This paper reports the results achieved in items c and d. Around the drillships iceberg are cleared away by standard towing procedures, 3. Near Hekja, the Zapata supply vessels FREEDOM SERVICE and PIONEER SERVICE were used to circle each berg with 3/4 mi. of floating polypropylene rope, catching the forward end and gripping the iceberg at the rear water line. Following the attachment procedure (taking about one hour) the captain would apply 10-110 tons of bollard pull. A major difficulty then arising is that many bergs are of low stability and will roll, slipping the tow hawser.

Impinging stream contactors provide a novel configuration for drying and/or gas/solid chemical reactions involving particulates. pastes or suspensions which can be dispersed in a flowing gas stream. Essentially they consist of one or more highly turbulent “ impingement ” zones formed by normal collision of two confined opposing jets in a channel or duct. Little information exists in the current literature on the flow and thermal characteristics of such flows. The objective of this paper is to present computational fluid dynamic predictions for confined two-dimensional opposing turbulent jets over a range of nozzle-to-nozzle separations and jet Reynolds numbers and superheated steam drying of panicles in such contactors. The standard k-E model is used to close the governing conservation equations. Some results on the prediction of single particle trajectories and drying in such flows are presented. Predictions are performed in two distinct pans. In the first part a hybrid. finite volume method bas...

A novel control strategy that combines model predictive control (MPC) with semi-active vibration control that uses a highly effective, energy-efficient, and stable piezoelectric transducer is proposed in this paper. Incorporating MPC into semi-active vibration control enables significant improvements in control performance and robustness. However, it is challenging to directly predict and optimize the input trajectory because the semi-active input has a state-dependent discontinuous nature. To realize effective optimal control, we need a strategy that can predict the discontinuous semi-active input trajectory in a reasonable manner and is computationally cost-efficient. The proposed method employs a prediction algorithm based on a tree data structure. The proposed algorithm achieves flexible prediction and optimization of a semi-active input trajectory with a simple tree traversal. In addition, the proposed method employs a switching criterion to minimize the computational cost and implement fast prediction and optimization. The proposed method is called predictive switching vibration control with tree-based formulation and optimization, or the PSTFO method. The simulation proved that the proposed PSTFO method can predict discontinuous semi-active input and realizes optimal vibration control performance and high robustness. In addition, the high control performance and robustness of the proposed method were experimentally validated.

Maritime rescue operations often involve extensive searches for drifting objects, typically life rafts or persons in the water, and search operations are directed based on computer predictions of drift trajectories. These predictions are based on estimates of local wind and wave conditions and, since there are uncertainties associated with these estimates the search area grows rapidly with time, and often within a few hours the area may be far larger than can be effectively searched by available aircraft and ships. This paper describes the development of a new tool for maritime search and rescue (SAR) activities, called a self locating datum marker buoy (DMB). It comprises an air deployable buoy that drifts with the same trajectory as a life raft (primarily driven by the wind) or as a person in the water (primarily driven by the surface current) depending on the configuration chosen prior to deployment. The buoy contains a GPS receiver and an ARGOS satellite transmitter so that it is able to relay near real-time position data to a rescue coordination center, and thus allows the search activities to be directed in a more focused, and successful manner. The development of the buoy is discussed in the paper, results of drift validation trials in conditions of high winds and currents are presented, and the impact of DIME data on search area predictions is shown.

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Research on ribonucleic acid (RNA) structures and functions benefits from easy-to-use tools for computational prediction and analyses of RNA three-dimensional (3D) structure. The SimRNAweb server version 2.0 offers an enhanced, user-friendly platform for RNA 3D structure prediction and analysis of RNA folding trajectories based on the SimRNA method. SimRNA employs a coarse-grained model, Monte Carlo sampling and statistical potentials to explore RNA conformational space, optionally guided by spatial restraints. Recognized for its accuracy in RNA 3D structure prediction in RNA-Puzzles and CASP competitions, SimRNA is particularly useful for incorporating restraints based on experimental data. The new server version introduces performance optimizations and extends user control over simulations and the processing of results. It allows the application of various hard and soft restraints, accommodating alternative structures involving canonical and noncanonical base pairs and unpaired residues, while also integrating data from chemical probing methods. Enhanced features include an improved analysis of folding trajectories, offering advanced clustering options and multiple analyses of the generated trajectories. These updates provide comprehensive tools for detailed RNA structure analysis. SimRNAweb v2.0 significantly broadens the scope of RNA modeling, emphasizing flexibility and user-defined parameter control. The web server is available at https://genesilico.pl/SimRNAweb.

Computer predictions of three-dimensional particle trajectories in gas turbines

A series of zinc-based catalysts was evaluated for their efficiency in decomposing formic acid into molecular hydrogen and carbon dioxide in the gas phase using quadrupole ion trap mass spectrometry experiments. The effectiveness of the catalysts in the series [(L)Zn(H)]+ , where L=2,2':6',2''-terpyridine (tpy), 1,10-phenanthroline (phen) or 2,2'-bipyrydine (bpy), was found to depend on the ligand used, which turned out to be fundamental in tuning the catalytic properties of the zinc complex. Specifically, [(tpy)Zn(H)]+ displayed the fastest reaction with formic acid proceeding by dehydrogenation to produce the zinc formate complex [(tpy)Zn(O2 CH)]+ and H2 . The catalysts [(L)Zn(H)]+ are reformed by decarboxylating the zinc formate complexes [(L)Zn(O2 CH)]+ by collision-induced dissociation, which is the only reaction channel for each of the ligands used. The decarboxylation reaction was found to be reversible, since the zinc hydride complexes [(L)Zn(H)]+ react with carbon dioxide yielding the zinc formate complex. This reaction was again substantially faster for L=tpy than L=phen or bpy. The energetics and mechanisms of these processes were modelled using several levels of density functional theory (DFT) calculations. Experimental results are fully supported by the computational predictions.

Intermolecular complexes between CHF3 and CO have been studied by ab initio calculations and IR matrix isolation spectroscopy. The computations at the MP2 and CCSD(T) levels of theory indicated five minima on the potential energy surface (PES). The most energetically favorable structure is the C(CO)-H(CHF3) coordinated complex ( Cs symmetry) with the stabilization energy of 0.84 kcal/mol as computed at the CCSD(T) level (with ZPVE and BSSE corrections). This is the only structure experimentally found in argon and krypton matrixes, whereas the weaker non-hydrogen-bonded complexes predicted by theory were not detected. The vibrational spectrum of this complex is characterized by a red-shift of the CF3 asymmetric stretching, splitting of the C-H bending mode, and blue-shifts of the C-H and C-O stretching vibrations as compared to the monomer molecules. The observed complexation-induced shifts of CHF3 and CO fundamentals are in good agreement with the computational predictions. It was shown that both MP2 and CCSD(T) calculations generally provided a reasonable description of the vibrational properties for the weak intermolecular complexes of fluoroform.

Rnf complexes are redox-driven ion pumps identified in diverse species from the domains Bacteria and Archaea, biochemical characterizations of which are reported for two species from the domain Bacteria. Here, we present characterizations of the redox-active subunits RnfG and RnfB from the Rnf complex of Methanosarcina acetivorans, an acetate-utilizing methane-producing species from the domain Archaea. The purified RnfG subunit produced in Escherichia coli fluoresced in SDS-PAGE gels under UV illumination and showed a UV-visible spectrum typical of flavoproteins. The Thr166Gly variant of RnfG was colorless and failed to fluoresce under UV illumination confirming a role for Thr166 in binding FMN. Redox titration of holo-RnfG revealed a midpoint potential of −129 mV for FMN with n = 2. The overproduced RnfG was primarily localized to the membrane of E. coli and the sequence contained a transmembrane helix. A topological analysis combining reporter protein fusion and computer predictions indicated that the C-terminal domain containing FMN is located on the outer aspect of the cytoplasmic membrane. The purified RnfB subunit produced in E. coli showed a UV-visible spectrum typical of iron-sulfur proteins. The EPR spectra of reduced RnfB featured a broad spectral shape with g values (2.06, 1.94, 1.90, 1.88) characteristic of magnetically coupled 3Fe-4S and 4Fe-4S clusters in close agreement with the iron and acid-labile sulfur content. The ferredoxin specific to the aceticlastic pathway served as an electron donor to RnfB suggesting this subunit is the entry point of electrons to the Rnf complex. The results advance an understanding of the organization and biochemical properties of the Rnf complex and lay a foundation for further understanding the overall mechanism in the pathway of methane formation from acetate.

By using computer software Gaussian 16 B.01, the optimized structure of complex formed by the heme ligand and Cr was obtained. The structural properties, infrared spectrum, UV-Vis absorption spectrum, binding energy and frontier molecular orbital levels of the complex were analyzed and compared with heme under the same level of calculation. Studies have predicted that the binding ability of heme ligand to iron is greater than that to chromium. However, the chemical stability of the complex formed by heme ligand and Cr is stronger than that formed by heme ligand and Fe.

Understanding ligand-protein recognition and interaction processes is of primary importance for structure-based drug design. Traditionally, several approaches combining docking and molecular dynamics (MD) simulations have been exploited to investigate the physicochemical properties of complexes of pharmaceutical interest. Even if the geometric properties of a modeled protein-ligand complex can be well predicted by computational methods, it is challenging to rank a series of analogues in a consistent fashion with biological data. In the unique beta-hydroxyacyl-ACP dehydratase of Plasmodium falciparum (PfFabZ), the application of standard molecular docking and MD simulations was partially sufficient to shed light on the activity of previously discovered inhibitors. Complementing docking results with atomistic simulations in the steered molecular dynamics (SMD) framework, we devised an in silico approach to study molecular interactions and to compare the binding characteristics of ligand analogues. We hypothesized an interaction model that both explained the biological activity of known ligands, and provided insight into designing novel enzyme inhibitors. Mimicking single-molecule pulling experiments, we used SMD-derived force profiles to discern active from inactive compounds for the first time. A new compound was designed and its biological activity toward the PfFabZ enzyme predicted. Finally, the computational predictions were experimentally confirmed, highlighting the robustness of the drug design approach presented herein.