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Dynamic responses of spherical and conical squeeze film bearings
Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.
Understanding crystallization in ambient environments is essential for scaling the fabrication of halide perovskite solar cells. Antisolvent-free perovskite deposition offers improved compatibility with high-throughput processing but introduces distinct crystallization dynamics relative to the more ubiquitous use of antisolvents in lab-scale perovskite fabrication. These dynamics are driven by interactions between solutes, solvent and the deposition environment. Using in situ wide-angle X-ray scattering during spin-coating and annealing, we demonstrate how relative humidity (RH) and oxygen, can be tuned to drive polytype evolution during ambient crystallization of formamidinium lead iodide to match that of inert synthesis and achieve comparable film and device quality. In an inert (N 2 ) environment, we find that perovskite films follow a well-established 2H → 3C phase transformation with a short period of coexistence of the 4H and 6H phase during heating. During crystallization in dry air (RH 0%), the added presence of oxygen leads to the dominance of 4H intermediate for an extended duration, establishing a 2H → 4H → 3C pathway. Introducing low humidity (RH 10%) suppresses the 4H phase to a short-lived intermediate above 100 °C, facilitating a more direct transition to the desired 3C phase and almost replicating the crystallization behavior observed under inert conditions. Interestingly, films crystallized under RH 10% show a lower onset temperature for the perovskite 3C phase than under N 2 . At higher humidity (RH 40%), the strong interaction of oxygen and moisture with iodoplumbates appears to stabilize higher order polytypes (4H and 6H). Devices fabricated under RH 10% achieve higher efficiency and enhanced stability compared to those produced under inert atmosphere. These findings provide mechanistic insight into crystallization pathways in different environments and provide a framework to transfer processes from inert to ambient conditions. The results highlight the critical role of controlled humidity in tuning antisolvent-free perovskite crystallization for scalable processing.
In the present investigation, a systematic study of the evolution of microstructure and crystallographic texture during hot deformation of Nb-1Zr-0.1C was carried out in the temperature range 1773-1973 K (1500-1700 °C) at different strain rates of 0.001, 0.01 and 0.1 s{sup −1}. The aim was to examine the mechanisms of dynamic recovery and recrystallization in a high-temperature range. A detailed microstructural analysis of the deformed samples was performed using the electron backscatter diffraction technique to study the occurrence and nature of various dynamic restoration processes; the different regimes of dynamic recovery and recrystallization were identified. The orientations of the dynamically recrystallized grains were found to be (001) .
In this paper the filament winding process was analyzed to relate process variables to structural parameters. An analytical model has been developed for a filament wound preform by determining the necessary geometric and kinematic conditions. An equation of motion of winding was developed to predict layer by layer geometry using the mandrel shape as the initial boundary condition. This model provides the laws of motion of the traverse stroke relative to the mandrel to ensure that the filament laydown is of the predetermined geodesic path over the mandrel, that the winding density is distributed over the mandrel in the prearranged manner, and that the winding build is being formed to reproduce the preassigned shape or contour of the preform. From this analysis, the winding process parameters can be controlled accordingly to produce any given shape. The analytical model was used to produce computer simulation of the winding process. The dynamic simulation of the winding process visualizes and inspects the layer by layer path of the tow and provides process variables required to produce preforms of optimum structural parameters.
Amorphous materials have attracted great interest in the scientific and technological fields. An amorphous solid usually forms under the externally driven conditions of melt-quenching, irradiation and severe mechanical deformation. However, its dynamic formation process remains elusive. Here we report the in situ atomic-scale observation of dynamic amorphization processes during mechanical straining of nanoscale silicon crystals by high resolution transmission electron microscopy (HRTEM). We observe the shear-driven amorphization (SDA) occurring in a dominant shear band. The SDA involves a sequence of processes starting with the shear-induced diamond-cubic to diamond-hexagonal phase transition that is followed by dislocation nucleation and accumulation in the newly formed phase, leading to the formation of amorphous silicon. The SDA formation through diamond-hexagonal phase is rationalized by its structural conformity with the order in the paracrystalline amorphous silicon, which maybe widely applied to diamond-cubic materials. Besides, the activation of SDA is orientation-dependent through the competition between full dislocation nucleation and partial gliding.
The present discussion deals with some theoretical aspects associated with the description of molecular rate processes in the presence of intense laser radiation, where the radiation actually interacts with the molecular dynamics. Whereas for weak and even moderately intense radiation, the absorption and stimulated emission of photons by a molecular system can be described by perturbative methods, for intense radiation, perturbation theory is usually not adequate. Limiting the analysis to the gas phase, an attempt is made to describe nonperturbative approaches applicable to the description of such processes (in the presence of intense laser radiation) as electronic energy transfer in molecular (in particular atom-atom) collisions; collision-induced ionization and emission; and unimolecular dissociation.
Silicon-chlorine-argon (Si-Cl 2 -Ar) atomic layer etching (ALE) is simulated using classical molecular dynamics (MD). The simulations provide a detailed view into the near-surface region during ALE processing. Bombardment of Ar + ions creates a mixed amorphous region that significantly differs from the picture of ideal ALE. There is also a significant change in the Si etch yield and the etch product distribution as a function of Ar + ion fluence. The Si etch yield is the highest at the beginning of the bombardment step but eventually decays to the physical sputtering yield. Atomic Cl and silicon chlorides are major etch products at the start of an ion bombardment step, but quickly decay. Atomic Si yields remain relatively constant as a function of Ar + ion fluence. As a result, a new schematic of Si-Cl 2 -Ar ALE is presented in order to emphasize the complex behavior observed in MD simulations.
The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.
Nonlinear beam dynamics optimization is essential in a low emittance storage ring design. Multi-objective optimization algorithms are needed in order to simultaneously optimize the dynamic aperture and the momentum aperture. In this study we demonstrate the application of a highly efficient stochastic optimization algorithm, the multi-generation Gaussian process optimizer (MG-GPO), to storage ring nonlinear dynamics optimization by successfully applying the method to the SPEAR3 upgrade lattice. It is shown that the new method, owing to its capability of selecting high rank candidates from a large number of trial solutions, converges significantly faster than the commonly used traditional algorithms, multi-objective genetic algorithms (MOGA) and particle swarm optimization (PSO).
The ability to observe dynamic chemical processes (e.g., signaling, transport, etc.) in vivo or in situ using nondestructive chemical imaging opens a new door to understanding the complex dynamics of developing biological systems. With the advent of “biology-on-a-chip” devices has come the ability to monitor dynamic chemical processes in a controlled environment, using these engineered habitats to capture key features of natural systems while allowing visual observation of system development. Having the capability to spatially and temporally map the chemical signals within these devices may yield new insights into the forces that drive biosystem development. Here, a porous membrane sealed microfluidic device was designed to allow normal microfluidic operation while enabling continuous, location specific sampling and chemical characterization by liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS). LMJ-SSP was used to extract fluids with nL-to-μL/min flow rates directly from selected areas of the microfluidic device without negatively impacting the device function. These extracts were subsequently characterized using MS. This technique was used to acquire MS images of the entirety of several multi-input microfluidic devices having different degrees of fluid mixing. LMJ-SSP MS imaging visualized the spatial distribution of chemical components within the microfluidic channels and could visualize chemical reactions occurring in the device. These microfluidic devices with a porous membrane wall are wholly compatible with the construction of biology-on-a-chip devices. This ultimately would enable correlation of biosystem physical structure with an evolving chemical environment
The Software Engineering Laboratory (SEL) has been operating for more than two decades in the Flight Dynamics Division (FDD) and has adapted to the constant movement of the software development environment. The SEL's Improvement Paradigm shows that process improvement is an iterative process. Understanding, Assessing and Packaging are the three steps that are followed in this cyclical paradigm. As the improvement process cycles back to the first step, after having packaged some experience, the level of understanding will be greater. In the past, products resulting from the packaging step have been large process documents, guidebooks, and training programs. As the technical world moves toward more modularized software, we have made a move toward more modularized software development process documentation, as such the products of the packaging step are becoming smaller and more frequent. In this manner, the QIP takes on a more spiral approach rather than a waterfall. This paper describes the state of the FDD in the area of software development processes, as revealed through the understanding and assessing activities conducted by the COTS study team. The insights presented include: (1) a characterization of a typical FDD Commercial Off the Shelf (COTS) intensive software development life-cycle process, (2) lessons learned through the COTS study interviews, and (3) a description of changes in the SEL due to the changing and accelerating nature of software development in the FDD.
A computational fluid dynamics model has been developed to predict the behavior of a printed strands during a novel material extrusion additive manufacturing and compression molding process. While the traditional additive manufacturing process enables control over the fiber orientation within the part, it would also result in high void content. On the other hand, compression molding produces parts with low porosity levels at rapid processing cycle time but lacks control over the microstructure. The novel additive manufacturing – compression molding (AM-CM) integrating both these processes offers control over both the microstructure and porosity to manufacturing high performance composite parts. The numerical model developed here enables to analyze the effect of processing parameters on the behaviour of printed layer that is subsequently compressed and to determine the optimal printing parameters for high-performance composite part design.
Nontyphoidal Salmonella is a leading cause of foodborne illness, with poultry representing a major source. Peracetic acid (PAA), a widely adopted antimicrobial in poultry processing, offers advantages over traditional disinfectants but has sparked interest in its combined use with other antimicrobials and potential resistance. This review evaluates the efficacy of PAA in mitigating Salmonella in combination with other food-grade antimicrobials, explores possible synergism, efficacy under varying treatment parameters, resistance development against PAA, and its role in resistance evolution. While PAA demonstrates broad-spectrum efficacy, its performance varies with environmental parameters; higher temperatures generally enhance antimicrobial action but also accelerate PAA degradation. Organic matter diminishes PAA efficacy by reactive quenching. Variability in concentration and contact time further influences outcomes. Despite its oxidative mode of action and presumed low risk for resistance, emerging studies indicate that Salmonella can develop adaptive tolerance and potential cross/coresistance following repeated or sublethal exposure to PAA. These adaptations may involve genetic upregulation of oxidative stress response pathways, efflux systems, and modifications in cell membrane integrity, raising concerns about the long-term sustainability of PAA use. Additionally, combinatorial treatments (e.g., PAA with UV-C, enzymes, or organic acids) show promise in enhancing efficacy while mitigating resistance risks. Despite recognition of PAA's safety and effectiveness, knowledge gaps remain regarding standardized resistance definitions, serotype-specific tolerance, and optimal intervention strategies in commercial settings. Therefore, there is a need for standardized testing protocols, robust studies on potential resistance, and further exploration of synergistic PAA applications to ensure sustained poultry product safety and public health protection.
It is proposed that the source for solar hard X-ray bursts may consist of a distribution of many small impulsively-heated kernels, each cooled by anomalous conduction, with lifetimes shorter than current burst data temporal resolution. The dynamic spectra of bursts are governed by the dynamic evolution of the kernel production process, such as magnetic-field dissipation in the tearing mode. An integral equation is formulated, the solution of which yields information on this kernel production process from dynamic burst spectra, for any kernel model.
Many modern adhesives, sealants, and coatings rely on the controlled transition from a liquid to a solid state by forming a three-dimensional cross-linked polymer network, often referred to as curing. The curing process, which is initiated by the mixing of reactive components or an external trigger, defines the structure of a network and further controls the final mechanical properties of cured materials. However, the curing mechanism is not fully understood yet due to the lack of experimental tools capable of directly probing the structure and dynamics of a network over relevant time- and length scales. Here, in this paper, we report the curing process of a commercial two-component methyl methacrylate (MMA) adhesive using in operando X-ray photon correlation spectroscopy (XPCS), a method that closely simulates the target manufacturing environment of the adhesive. The results are then integrated with those obtained by rheology, differential scanning calorimetry (DSC), and transmission electron microscopy to establish the structure–dynamics–process–property relationship. The XPCS results identify four distinct stages in the curing process after the mixing, extrusion, and deposition of the acrylic adhesive: (i) At a cure time (or “aging time”, t age ) of less than 1 min, nanodomains of polymerized MMA are formed within a liquid monomeric MMA matrix. The average size is several nm and remains constant over t age , while the dynamics of the nanodomains are slowed down with t age due to an increase in the viscosity of the MMA matrix. (ii) After t age > 1 min, the size of the nanodomains increases with t age until the gel point (= 6.3 min after mixing as determined by rheology). The dynamics of the nanodomains also increase due to the heat generated by the exothermic reaction. (iii) At the gel point, the nanodomains begin to interconnect each other, resulting in a network structure with a characteristic length of about 100 nm. This characteristic network size does not change for the rest of the curing process up to t age = 500 min. The dynamics of the network structure, however, show a rapid slowing down with t age up to t age ≈ 12 min, corresponding to the onset of vitrification (as determined by rheology). (iv) At t age > 12 min, when the DSC and rheology data can no longer provide meaningful information, the XPCS data show a further slowing down of the network dynamics associated with vitrification. Our results provide rich and complex insights into the physics and material design of thermosets in commercially relevant processes, which are essential for future industrial applications.
A system engineering methodology is described which enables users, particulary NASA and DOD, to accommodate changing needs; incorporate emerging technologies; identify, quantify, and manage system risks; manage evolving functional requirements; track the changing environment; and reduce system life-cycle costs. The approach is a concurrent, dynamic one which starts by constructing a performance model defining the required system functions and the interrelationships. A detailed probabilistic risk assessment of the system elements and their interrelationships is performed, and quantitative analysis of the reliability and maintainability of an engineering system allows its different technical and process failure modes to be identified and their probabilities to be computed. Decision makers can choose technical solutions that maximize an objective function and minimize the probability of failure under resource constraints.
This paper presents the interim results from the Software Engineering Laboratory's (SEL) Reuse Study. The team conducting this study has, over the past few months, been studying the Generalized Support Software (GSS) domain asset library and architecture, and the various processes associated with it. In particular, we have characterized the process used to configure GSS-based attitude ground support systems (AGSS) to support satellite missions at NASA's Goddard Space Flight Center. To do this, we built detailed models of the tasks involved, the people who perform these tasks, and the interdependencies and information flows among these people. These models were based on information gleaned from numerous interviews with people involved in this process at various levels. We also analyzed effort data in order to determine the cost savings in moving from actual development of AGSSs to support each mission (which was necessary before GSS was available) to configuring AGSS software from the domain asset library. While characterizing the GSS process, we became aware of several interesting factors which affect the successful continued use of GSS. Many of these issues fall under the subject of evolving technologies, which were not available at the inception of GSS, but are now. Some of these technologies could be incorporated into the GSS process, thus making the whole asset library more usable. Other technologies are being considered as an alternative to the GSS process altogether. In this paper, we outline some of issues we will be considering in our continued study of GSS and the impact of evolving technologies.