Identical Initial States Research Articles

Experimental study on compression behaviours of compacted sandy loam using a Modified State Surface Approach

It is essential to study the deformation of unsaturated soil to predict the settlement of constructed embankments and foundations under precipitation and external loadings. This study conducted suction-controlled and stress-controlled oedometer tests on compacted sandy loam. The void ratio and degree of saturation were measured to study the deformation behaviours of unsaturated soil. The acquired data were analyzed using a modified state surface approach (MSSA). It was found that for the samples with an identical initial state, a unique state surface can be employed to describe the change of void ratio in an e-σ v’-s space, which consists of an elastic session and a plastic collapsible session. After yielding, the LC yield curve expands along the plastic collapsible surface with increasing loading or decreased suction, accompanied by irrecoverable plastic deformation. Along the hydraulic wetting paths (suction decreasing), the soil exhibits expansive deformation in the elastic surface but collapses into plastic collapsible after yielding. Differing from deformation behaviours, this study also demonstrated that the degree of saturation (S r) cannot be plotted in a unique surface in S r-σ v’-s space regarding hydraulic wetting and mechanical compression. This can be interpreted by different mechanisms of increasing S r by adsorbing water and mechanical compression.

Discrete-Time-Distributed Adaptive ILC With Nonrepetitive Uncertainties and Applications to Building HVAC Systems

Aiming to addressing the nonrepetitive uncertainties of multiagent systems, this work proposes a discrete-time-distributed adaptive iterative learning control (DDAILC) scheme for an output consensus problem, where two fundamental requirements in the traditional distributed iterative learning control (ILC) methods, i.e., the identical initial states and the repetitive desired trajectories, are removed. Furthermore, the algorithm design and analysis are directly aimed at discrete-time nonlinear multiagent systems, rather than continuous-time ones, to meet the needs of practical implementations. The iteration-varying trajectory of the virtual leader is included in the learning control protocol for a compensation. The adaptive parameter-updating law works along the iteration dimension by using a general consensus error that contains the output data of adjacent agents. To ensure the estimation of the control gain to be nonzero, a semisaturator is utilized in the parameter-updating law. The convergence of the output consensus is shown rigorously. Both numerical and practical examples are used to test the theoretical results. Moreover, the DDAILC efficiently improves performance of the building heating, ventilation, and air conditioning (HVAC) system by utilizing both the distributed topology and the repetitive dynamic characteristic.

Complex Structure Modification and Improvement of Properties of Aluminium Casting Alloys with Various Silicon Content

The possibility of using complex structure modification for aluminium casting alloys’ mechanical properties improvement was studied. The fluxes widely used in the industry are mainly intended for the modification of a single structural component of Al–Si alloys, which does not allow unifying of the modification process in a production environment. Thus, a new modifying flux that has a complex effect on the structure of Al–Si alloys has been developed. It consists of the following components: TiO2, containing a primary α-Al grain size modifier; BaF2 containing a eutectic silicon modifier; KF used to transform titanium and barium into the melt. The effect of the complex titanium dioxide-based modifier on the macro-, microstructure and the mechanical properties of industrial aluminium–silicon casting alloys containing 5%, 6%, 9%, 11% and 17% Si by weight was studied. It was found that the tensile strength (σB) of Al–Si alloys exceeds the similar characteristics for the alloys modified using the standard sodium-containing flux to 32%, and the relative elongation (δ) increases to 54%. The alloys’ mechanical properties improvement was shown to be the result of the flux component’s complex effect on the macro- and microstructure. The effect includes the simultaneous reduction in secondary dendritic arm spacing due to titanium, the refinement and decreasing size of silicon particles in the eutectic with barium and potassium, and the modifying of the primary silicon. The reliability of the studies was confirmed using up-to-date test systems, a significant amount of experimental data and the repeatability of the results for a large number of samples in the identical initial state.

Deformation Behavior of Saturated Marine Silt under Principal Stress Rotation as Induced by Wave Loading

An experimental study aimed at providing insights into the cyclic deformation behavior of saturated marine silt under principal rotation, as induced by wave loading, is presented. Using the GDS hollow cylinder apparatus, a series of undrained tests are performed and the specimens at identical initial states are subjected to combined axial–torsional cyclic loading that imposes different levels of stress rotation. The cumulative generalized shear strain γg is used to describe the deformation of the silt under complex stress paths. The test results show that the cumulative generalized shear strain is significantly dependent on the cyclic stress ratio (CSR) and cyclic loading amplitude ratio δ. The cumulative generalized shear strain increases with the increase in CSR and decreases with the increase in δ. The development trend of γg can be well predicted through the correct Monismith model in the non-liquefaction silt, with a low error that is generally less than 10%.

Data‐based iterative learning mechanism for unknown input‐output coupling parameters/matrices

SummaryIn this paper, we explore how to get the information of input‐output coupling parameters (IOCPs) for a class of uncertain discrete‐time systems by using iterative learning technique. Firstly, by taking advantage of repetitiveness of control system and informative input and output data, we design an iterative learning scheme for unknown IOCPs. It is shown that we can get the exact values of IOCPs one by one through running the repetitive system T+1 times if the control system is with identical initial state and noise free. Secondly, we give the iterative learning scheme for unknown IOCPs in the presence of measurement noise, system noise, or initial state drift and analyze the influence factors on the performance of developed iterative learning scheme. Meanwhile, we introduce the maximum allowable control deviation into the iterative learning mechanism to minimize the negative impact of noise on the performance of learning scheme and to enhance the robust of iterative learning scheme. Thirdly, for a class of multiple‐input–multiple‐output systems, we also develop iterative learning mechanism for unknown input‐output coupling matrices. Finally, an illustrative example is given to demonstrate the effectiveness of proposed iterative learning scheme.

Direct visualization of the E. coli Sec translocase engaging precursor proteins in lipid bilayers.

Escherichia coli exports proteins via a translocase comprising SecA and the translocon, SecYEG. Structural changes of active translocases underlie general secretory system function, yet directly visualizing dynamics has been challenging. We imaged active translocases in lipid bilayers as a function of precursor protein species, nucleotide species, and stage of translocation using atomic force microscopy (AFM). Starting from nearly identical initial states, SecA more readily dissociated from SecYEG when engaged with the precursor of outer membrane protein A as compared to the precursor of galactose-binding protein. For the SecA that remained bound to the translocon, the quaternary structure varied with nucleotide, populating SecA2 primarily with adenosine diphosphate (ADP) and adenosine triphosphate, and the SecA monomer with the transition state analog ADP-AlF3. Conformations of translocases exhibited precursor-dependent differences on the AFM imaging time scale. The data, acquired under near-native conditions, suggest that the translocation process varies with precursor species.

Cyclic Resistance of a Loose Sand Subjected to Rotation of Principal Stresses

An experimental study aimed at providing insights into the effects of the inclination of principal stress directions with respect to the bedding plane and the role of principal stress rotation on the cyclic resistance of sands is presented. A new hollow cylinder torsional shear device commissioned at Carleton University was used to conduct the experiments in water-deposited Fraser River sand. Specimens at identical initial states were subjected to a constant amplitude cyclic shear stress along loading paths that impose different levels of stress rotation. Cyclic resistance decreased significantly as the maximum orientation of the major principal stress increased to approximately 45°–60°, but it increased with further rotation. This is contrary to the conventional idea according to which the weakest response is expected when the loading causes larger principal stress rotation and/or when the major principal stress is aligned with the bedding planes. The alignment of the plane of maximum shear stress toward and stronger time history of shear stress on the horizontal bedding planes lead to increased liquefaction susceptibility. The nature of shear stress on the bedding planes appears more critical than the alignment of the major principal stress along the bedding planes during cyclic loading. Test results also suggest that cyclic simple shear tests on the basis of stress rotation would represent a lower bound or closer to lower bound resistance. Thus, cyclic simple shear tests provide a convenient means of determining the cyclic resistance and the obtained resistance can be considered a conservative measure if field loading conditions deviate from that in simple shear.

Effect of sample size on the response of DEM samples with a realistic grading

This paper shows that for DEM simulations of triaxial tests using samples with a grading that is representative of a real soil, the sample size significantly influences the observed material response. Four DEM samples with identical initial states were produced: three cylindrical samples bounded by rigid walls and one bounded by a cubical periodic cell. When subjected to triaxial loading, the samples with rigid boundaries were more dilative, stiffer and reached a higher peak stress ratio than the sample enclosed by periodic boundaries. For the rigid-wall samples, dilatancy increased and stiffness decreased with increasing sample size. The periodic sample was effectively homogeneous. The void ratio increased and the contact density decreased close to the rigid walls. This heterogeneity reduced with increasing sample size. The positions of the critical state lines (CSLs) of the overall response in e-log p′ space were sensitive to the sample size, although no difference was observed between their slopes. The critical states of the interior regions of the rigid-wall-bounded samples approached that of the homogeneous periodic sample with increasing sample size. The ultimate strength of the material at the critical state is independent of sample size.

Information-theoretic lower bound on energy cost of stochastic computation

Physical systems are often simulated using a stochastic computation where different final states result from identical initial states. Here, we derive the minimum energy cost of simulating a data sequence of a general physical system by stochastic computation. We show that the cost is proportional to the difference between two information-theoretic measures of complexity of the data—the statistical complexity and the predictive information . We derive the difference as the amount of information erased during the computation. Finally, we illustrate the physics of information by implementing the stochastic computation as a Gedanken experiment with a Szilard-type engine. The results create a new link between thermodynamics, information theory and complexity.

An Intercomparison of T-REX Mountain-Wave Simulations and Implications for Mesoscale Predictability

Numerical simulations of flow over steep terrain using 11 different nonhydrostatic numerical models are compared and analyzed. A basic benchmark and five other test cases are simulated in a two-dimensional framework using the same initial state, which is based on conditions during Intensive Observation Period (IOP) 6 of the Terrain-Induced Rotor Experiment (T-REX), in which intense mountain-wave activity was observed. All of the models use an identical horizontal resolution of 1 km and the same vertical resolution. The six simulated test cases use various terrain heights: a 100-m bell-shaped hill, a 1000-m idealized ridge that is steeper on the lee slope, a 2500-m ridge with the same terrain shape, and a cross-Sierra terrain profile. The models are tested with both free-slip and no-slip lower boundary conditions. The results indicate a surprisingly diverse spectrum of simulated mountain-wave characteristics including lee waves, hydraulic-like jump features, and gravity wave breaking. The vertical velocity standard deviation is twice as large in the free-slip experiments relative to the no-slip simulations. Nevertheless, the no-slip simulations also exhibit considerable variations in the wave characteristics. The results imply relatively low predictability of key characteristics of topographically forced flows such as the strength of downslope winds and stratospheric wave breaking. The vertical flux of horizontal momentum, which is a domain-integrated quantity, exhibits considerable spread among the models, particularly for the experiments with the 2500-m ridge and Sierra terrain. The differences among the various model simulations, all initialized with identical initial states, suggest that model dynamical cores may be an important component of diversity for the design of mesoscale ensemble systems for topographically forced flows. The intermodel differences are significantly larger than sensitivity experiments within a single modeling system.

Incoherent Control of Quantum Systems With Wavefunction-Controllable Subspaces via Quantum Reinforcement Learning

In this paper, an incoherent control scheme for accomplishing the state control of a class of quantum systems which have wavefunction-controllable subspaces is proposed. This scheme includes the following two steps: projective measurement on the initial state and learning control in the wavefunction-controllable subspace. The first step probabilistically projects the initial state into the wavefunction-controllable subspace. The probability of success is sensitive to the initial state; however, it can be greatly improved through multiple experiments on several identical initial states even in the case with a small probability of success for an individual measurement. The second step finds a local optimal control sequence via quantum reinforcement learning and drives the controlled system to the objective state through a set of suitable controls. In this strategy, the initial states can be unknown identical states, the quantum measurement is used as an effective control, and the controlled system is not necessarily unitarily controllable. This incoherent control scheme provides an alternative quantum engineering strategy for locally controllable quantum systems.

Influence of generalized initial state and principal stress rotation on the undrained response of sands

The dependence of the undrained behaviour of sand on the initial stress state and the orientation of principal stresses with respect to the bedding planes is assessed under generalized loading paths using hollow cylinder torsional shear tests. The undrained tests were carried out using displacement-controlled loading to confidently capture the post-peak strain-softening response. Undrained behaviour of sands under identical initial states is shown to be dependent on the direction of principal stresses, during and prior to undrained shear, in relation to the direction of bedding planes. The minimum undrained strength of the strain-softening sand is found to be highly influenced by the initial stress state (confining stress, direction of principal stresses, and static shear), even though the friction angle mobilized at the instant of minimum strength is unique. A mere rotation of principal stresses at constant deviator stress alone can lead to a strain-softening response that may culminate in limited or unlimited flow deformation. The susceptibility of sand to liquefaction due to stress rotation increases as the direction of the major principal stress approaches the orientation of the bedding plane. The potential for flow deformation is strongly dependent on the direction of the major principal stress in relation to the bedding planes, and the steady state strength is not uniquely related to the void ratio alone.Key words: liquefaction, hollow cylinder torsion test, principal stress direction, static shear, steady state strength, minimum undrained strength.

Influence of Specimen-Reconstituting Method on the Undrained Response of Sand

Abstract An experimental study aimed at a direct comparison of the undrained behavior of sand using specimens reconstituted by different techniques is presented. It is shown that at identical initial void ratio and effective stress state, the moist-tamped sand is potentially liquefiable, but in the water-deposited state may even be dilative. Water-deposited specimens are shown to be very uniform in contrast to the large nonuniformities that usually occur on moist tamping, rendering their results questionable from the standpoint of laboratory element tests. A direct comparison of the behavior of truly undisturbed sand specimens retrieved by in-situ ground freezing and their corresponding reconstituted counterparts after consolidating to identical initial states is also presented in support of the contention that the fabric that ensues on water pluviation closely simulates that of the natural alluvial and hydraulic fill sands, enabling the use of reconstituted specimens as substitutes for the expensive undisturbed frozen specimens for material characterization.

Loss of quantum-mechanical coherence in a measurement process.

A quantum-mechanical measurement process is analyzed in terms of a model Hamiltonian describing the interaction between a quantum system (a ``particle'') and a macroscopic apparatus (a ``detector''), which is assumed to be made up of N two-level elementary constituents (``molecules''). The description of the molecule locations introduces an effective fluctuating coupling constant, and this provokes a loss of quantum-mechanical coherence in the limit of large N. It is argued that coherence is lost statistically, as a result of the interaction: The collapse of the wave function is indeed obtained when the same experiment is performed many times, as a result of the microscopic differences among macroscopically identical initial states of the detector. In this way, insight is obtained into the mechanism engendering the loss of coherence suffered by a quantum-mechanical system when interacting with a macroscopic apparatus, and the concept of ``wave-function collapse'' is replaced by that of a statistically defined dephasing process. No classical behavior of the detection system is postulated and the presence of no external observer is required.