Column Span Research Articles

BEHAVIOR OF FLAT REINFORCED-CONCRETE COLUMN SIZE (15x30) CM TO AXIAL CYCLIC LOADING : COMPARATION STUDY COLUMN WITH REINFORCEMENT AND STEEL PROFILE

This research discusses the behavior of flat columns with the comparison of reinforced-concrete columns and IWF steel reinforcement. The research object took 4 column samples with a column size of 15x30 cm by comparing the reinforced-concrete column and concrete columns with IWF steel reinforcement. This study conducted comparisons with experimental tests, column capacity theory calculations, and calculations with the ANSYS19.2 program. The purpose of this study was to obtain the maximum axial load result, shorten the column, the relationship between stress and strain of the column, failure pattern of the column, and the ability of the column to withstand the number of floors in the sample of the reinforced-concrete column and concrete columns with IWF steel reinforcement. The results of the average maximum axial load of the test object for each sample column in the experimental test for K1 is 119,6 tons, K2 is 146,18 tons, K3 is 146,6 tons, and K4 is 167,46 tons, the maximum axial load in the column capacity calculation for column sample K1 is 130 tons, K2 is 159 tons, K3 is 157 tons, and K4 is 180 tons, and the maximum axial load in the ANSYS 19.2 program for column sample K1 is 122,7 tons, K2 is 138,86 tons, K3 is 150,14 tons, and K4 is 159,62 tons. The failure pattern occurred in column sample K1 is in the column span area, for sample K2 in the column span and pedestal area, the K3 column in the pedestal area, and the K4 column in the pedestal area. K1 column sample withstand 2-floors, K2 and K3 columns withstand 3-floors, and K4 column withstand 4-floors.

Bridging Direct and Indirect Data-Driven Control Formulations via Regularizations and Relaxations

In this article, we discuss connections between sequential system identification and control for linear time-invariant systems, often termed indirect data-driven control, as well as a contemporary direct data-driven control approach seeking an optimal decision compatible with recorded data assembled in a Hankel matrix and robustified through suitable regularizations. We formulate these two problems in the language of behavioral systems theory and parametric mathematical programs, and we bridge them through a multicriteria formulation trading off system identification and control objectives. We illustrate our results with two methods from subspace identification and control: namely, subspace predictive control and low-rank approximation, which constrain trajectories to be consistent with a nonparametric predictor derived from (respectively, the column span of) a data Hankel matrix. In both cases, we conclude that direct and regularized data-driven control can be derived as convex relaxation of the indirect approach, and the regularizations account for an implicit identification step. Our analysis further reveals a novel regularizer and a plausible hypothesis explaining the remarkable empirical performance of direct methods on nonlinear systems.

Comparative study on design of steel structures and RCC frame structures based on column span

In today’s generation time has more value than money and we have a great extent of construction techniques too that are demanding on the duration of construction. Steel Structural buildings are considered as a revolution in the new construction era due to its quick erection method. To have a prudent and effective structure design the most ideal route is to choose the kind of construction relying upon the suitable conditions and functional requirements. “The Comparative study on design of Steel Structures and RCC frame Structures based on columns span” will help us to choose the kind of construction which ideally suits the conditions and type of structure. This study’s major aim is based on the key factor i.e. span of the column, which can also play a major role along with the height of the building in design and analysis of a structure which in turn on the cost of the building. The scope of this article is based on comparative study between design, analysis and cost of construction for RCC Structure and Steel Structure in long span and short span of columns. In this project the design & analysis of G + 8 RCC Structure and Steel Structure are done using ETABS-2018 software.

Detection of the Number of Signals by Signal Subspace Matching

We present a novel and computationally simple solution to the problem of detecting the number of signals, which is applicable to both white and colored noise, and to a very small number of samples. The solution is based on a novel and non-asymptotic goodness-of-fit metric, referred to as signal subspace matching (SSM), which is aimed at matching a model-based signal subspace to its sampled-data-based counterpart. We form a set of hypothesized signal subspace models, with the $k$ -th model being a projection matrix composed of the $k$ leading eigenvectors of the sample-covariance matrix. This set of hypothesized models is compared to their sampled-data-based counterpart – a projection matrix constructed from the sampled data – via the SSM metric, and the model minimizing this metric is selected. We show that this solution involves the principal angles between the column span of the model and the column span of the model. We prove the consistency of this solution for the high signal-to-noise-ratio limit and for the large-sample limit. The large-sample consistency is shown to be conditioned on the signal-to-noise ratio (SNR) being higher than a a certain threshold. Simulation results, demonstrating the performance of the solution for both colored and white noise, are included.

Geometry and topology of symmetric point arrangements

We investigate point arrangements vi∈Rd,i∈{1,...,n} with certain prescribed symmetries. The arrangement space of v is the column span of the matrix in which the vi are the rows. We characterize properties of v in terms of the arrangement space, e.g. we characterize whether an arrangement possesses certain symmetries or whether it can be continuously deformed into another arrangement while preserving symmetry in the process. We show that whether a symmetric arrangement can be continuously deformed into its mirror image depends non-trivially on several factors, e.g. the decomposition of its representation into irreducible constituents, and whether we are in even or odd dimensions.

Rate-Optimal Streaming Codes for Channels With Burst and Random Erasures

In this paper, we design erasure-correcting codes for channels with burst and random erasures, when a strict decoding delay constraint is in place. We consider the sliding-window-based packet erasure model proposed by Badr et al., where any time-window of width $w$ contains either up to $a$ random erasures or an erasure burst of length at most $b$ . One needs to recover any erased packet with a strict decoding delay deadline of $\tau $ , where erasures are as per the channel model. Presently existing rate-optimal constructions in the literature require, in general, a field-size which grows exponential in $\tau $ , as long as $\frac {a}{\tau }$ remains a constant. In this work, we present a new rate-optimal code construction covering all channel and delay parameters, which requires an $O(\tau ^{2})$ field-size. As a special case, when $(b-a)=1$ , we have a field-size linear in $\tau $ . We also present two other constructions having linear field-size, under certain constraints on channel and decoding delay parameters. As a corollary, we obtain low field-size, rate-optimal convolutional codes for any given column distance and column span. Simulations indicate that the newly proposed streaming code constructions offer lower packet-loss probabilities compared to existing schemes, for selected instances of Gilbert-Elliott and Fritchman channels.

Optimal Streaming Codes for Channels With Burst and Arbitrary Erasures

This paper considers transmitting a sequence of messages (streaming messages) over a packet erasure channel. In each time slot, the source constructs a packet based on the current and the previous messages and transmits the packet, which may be erased when the packet travels from the source to the destination. Every source message must be recovered perfectly at the destination subject to a fixed decoding delay. We assume that the channel loss model introduces either one burst erasure or multiple arbitrary erasures in any fixed-sized sliding window. Under this channel loss assumption, we fully characterize the maximum achievable rate by constructing streaming codes that achieve the optimal rate. In addition, our construction of optimal streaming codes implies the full characterization of the maximum achievable rate for convolutional codes with any given column distance, column span, and decoding delay. Numerical results demonstrate that the optimal streaming codes outperform existing streaming codes of comparable complexity over some instances of the Gilbert–Elliott channel and the Fritchman channel.

Structural analysis of reinforced concrete mansard roof structures according to different structural plans

In this study, analysis and evaluations were carried in order to determine the optimum conditions of reinforced concrete mansard roof applications. In total 96 mansard and 24 non mansard structure analysis were performed. The constructed models are symmetrical from all directions and it is modeled under the minimum conditions allowed by the regulation. As the column span, the distance between the columns was determined as 4 meters. The span conditions were determined as 3 spans, 4 spans, 5 spans and 6 spans by evaluating the parcel sizes and zoning conditions. Thus, a total of 120 calculation models were created. The base shear force, column moments and the maximum top displacement values were discussed in concordance with these calculations. As a result of the analysis, the graphical values of the mansard buildings were examined along with the non mansard buildings from the 3rd floor to the 8th floor, according to the zoning plan. In this study, graphs of parcels, span values and the number of storeys were drawn by keeping the values constant, and evaluations were made on the same graphs with and non mansard. In addition, by looking at the movements of the graphs obtained from this study on the same series, equations were adapted to the graphs and the series created with these equations were expanded and stochastic parabolic cones were formed at the shear force for 10 storeys, in the column moments. The mean values for the top displacement chart were taken and when the 20-storey displacement value was placed on this curve, it was determined that it appeared at a point very close to the estimating equation curve. Based on the analysis results, it is understood that it is possible to create a set of estimations for different number of storeys and plans.

Predicting the Required Volume Need for Architectural Work Using Artificial Neural Networks in Hospital Buildings

Decision-making in construction design has an important role. The need for estimation tools of planning and project management aspects needs to develop. This paper discussed the benefits of artificial neural network methodology to overcome the problem of estimated the needs of the volume of wall paired, ceiling worked pairing, and ceramic floor pairing for architectural work at the designed stage of the building. The average architecture cost of state building is 29%-51% of total construction value. Data from 15 projects was used for being trained and tested by Artificial Neural Network (ANN) methods with 5 design input variables. The ANN helped to estimate the value of volume requirement on the architectural working of Pratama Hospital building project in remote areas of Indonesia. Those input variables include building area, average column span distance, the height of the building, the shape of the building, and a number of inpatient rooms. From ANN simulation, the best empirical equation of P2V5 modeling was used to predict the need of hospital architecture work volume at conceptual stage with best ANN structure 5-9-3 (5 input variables, 1 hidden layer with 9 neurons and 3 output) with result of estimation accuracy a maximum of 96.40% was reached.

Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error

It is well understood that dynamic instability is among the primary drivers of forecast uncertainty in chaotic, physical systems. Data assimilation techniques have been designed to exploit this phenomenon, reducing the effective dimension of the data assimilation problem to the directions of rapidly growing errors. Recent mathematical work has, moreover, provided formal proofs of the central hypothesis of the assimilation in the unstable subspace methodology of Anna Trevisan and her collaborators: for filters and smoothers in perfect, linear, Gaussian models, the distribution of forecast errors asymptotically conforms to the unstable-neutral subspace. Specifically, the column span of the forecast and posterior error covariances asymptotically align with the span of backward Lyapunov vectors with nonnegative exponents. Earlier mathematical studies have focused on perfect models, and this current work now explores the relationship between dynamical instability, the precision of observations, and the evolution of forecast error in linear models with additive model error. We prove bounds for the asymptotic uncertainty, explicitly relating the rate of dynamical expansion, model precision, and observational accuracy. Formalizing this relationship, we provide a novel, necessary criterion for the boundedness of forecast errors. Furthermore, we numerically explore the relationship between observational design, dynamical instability, and filter boundedness. Additionally, we include a detailed introduction to the multiplicative ergodic theorem and to the theory and construction of Lyapunov vectors. While forecast error in the stable subspace may not generically vanish, we show that even without filtering, uncertainty remains uniformly bounded due its dynamical dissipation. However, the continuous reinjection of uncertainty from model errors may be excited by transient instabilities in the stable modes of high variance, rendering forecast uncertainty impractically large. In the context of ensemble data assimilation, this requires rectifying the rank of the ensemble-based gain to account for the growth of uncertainty beyond the unstable and neutral subspace, additionally correcting stable modes with frequent occurrences of positive local Lyapunov exponents that excite model errors.

Layered Constructions for Low-Delay Streaming Codes

We propose a new class of error correction codes for low-delay streaming communication. We consider an online setup where a source packet arrives at the encoder every $M$ channel uses, and needs to be decoded with a maximum delay of $T$ packets. We consider a sliding-window erasure channel --- $\cC(N,B,W)$ --- which introduces either up to $N$ erasures in arbitrary positions, or $B$ erasures in a single burst, in any window of length $W$. When $M=1$, the case where source-arrival and channel-transmission rates are equal, we propose a class of codes --- MiDAS codes --- that achieve a near optimal rate. Our construction is based on a {\em layered} approach. We first construct an optimal code for the $\cC(N=1,B,W)$ channel, and then concatenate an additional layer of parity-check symbols to deal with $N>1$. When $M > 1$, the case where source-arrival and channel-transmission rates are unequal, we characterize the capacity when $N=1$ and $W \ge M(T+1),$ and for $N>1$, we propose a construction based on a layered approach. Numerical simulations over Gilbert-Elliott and Fritchman channel models indicate significant gains in the residual loss probability over baseline schemes. We also discuss the connection between the error correction properties of the MiDAS codes and their underlying column distance and column span.

What to Expect When You Are Expecting on the Grassmannian

Consider an incoming sequence of vectors, all belonging to an unknown subspace $\operatorname{S}$, and each with many missing entries. In order to estimate $\operatorname{S}$, it is common to partition the data into blocks and iteratively update the estimate of $\operatorname{S}$ with each new incoming measurement block. In this paper, we investigate a rather basic question: Is it possible to identify $\operatorname{S}$ by averaging the column span of the partially observed incoming measurement blocks on the Grassmannian? We show that in general the span of the incoming blocks is in fact a biased estimator of $\operatorname{S}$ when data suffers from erasures, and we find an upper bound for this bias. We reach this conclusion by examining the defining optimization program for the Fr\'{e}chet expectation on the Grassmannian, and with the aid of a sharp perturbation bound and standard large deviation results.

Exploring the complexity of the integer image problem in the max-algebra

We investigate the complexity of the problem of finding an integer vector in the max-algebraic column span of a matrix, which we call the integer image problem. We show some cases where we can determine in strongly polynomial time whether such an integer vector exists, and find such an integer vector if it does exist. On the other hand we also describe a group of related problems each of which we prove to be NP-hard. Our main results demonstrate that the integer image problem is equivalent to finding a special type of integer image of a matrix satisfying a property we call column typical. For a subclass of matrices this problem is polynomially solvable but if we remove the column typical assumption then it becomes NP-hard.

Biaxial bending of slender HSC columns and tubes filled with concrete under short- and long-term loads: I) Theory

An analytical method that calculates both the short- and long-term response of slender columns made of high-strength concrete (HSC) and tubes filled with concrete with generalized end conditions and subjected to transverse loads along the span and axial load at the ends (causing a single or double curvature under uniaxial or biaxial bending) is presented. The proposed method, which is an extension of a method previously developed by the authors, is capable of predicting not only the complete load-rotation and load-deflection curves (both the ascending and descending parts) but also the maximum load capacity. The columns that can be analyzed include solid and hollow (rectangular, circular, oval, C-, T-, L-, or any arbitrary shape) cross sections and columns made of circular and rectangular steel tubes filled with HSC. The fiber method is used to calculate the moment-curvature diagrams at different levels of the applied axial load (i.e., the M-P-φ curves), and the Gauss method of integration (for the sum of the contributions of the fibers parallel to the neutral axis) is used to calculate the lateral rotations and deflections along the column span. Long-term effects, such as creep and shrinkage of the concrete, are also included. However, the effects of the shear deformations and torsion along the member are not included. The validity of the proposed method is presented in a companion paper and compared against the experimental results for over seventy column specimens reported in the technical literature by different researchers.

Finite Element Analysis and Parametric Study on the Stability of Dendritic Column

With the rapid development of the Chinese railway in recent years, the construction of so many large railway stations are needed. Because the roof and the canopy should be convenient for the passengers and goods to get through, the column spacing and span is large. In order to achieve the functional and aesthetic requirements of the railway stations, the dendritic column is developed. Dendritic structure is the building structure which is designed by the principle of zoology and undertaking force of tree among nature. It has particular appreciation and practicability. In order to determine the critical load and buckling behavior of the dendritic column from stable balance to unstable balance condition, the finite element model is established by the finite element analysis program ANSYS. And the linear overall stability, geometrical nonlinear overall stability, geometrical and material nonlinear overall stability were studied. Through changing such factors as the stiffness ratio and the height ratio between the trunk and the branch, span to height ratio of branch, etc., the authors further studied the nonlinear stability behavior of this new type structure. It is showed that the ultimate bearing capacity of the Y-shape column is high. And we got the conclusion that how these three parameters influence the ultimate bearing capacity of the dendritic column. And the results can offer reference for the design of the dendritic column. Your manuscript will be reduced by approximately 20% by the publisher. Please keep this in mind when designing your figures and tables etc.

Experiment and non-linear analysis of stainless steel columns having variable cross-sections

A useful numerical scheme, based on finite difference technique, has been devised and used to trace the load-deflection curves (equilibrium configuration paths) of a column that has highly non-linear stress-strain curves. Two theorems of Thompson and Hunt are used to interpret the existence of critical load for the column from those load-deflection curves. To make the study more comprehensive, a varying cross-section has been considered along the column's span. The devised method can be used to calculate buckling loads of any column having varying cross-section together with material non-linearity. To prove the fruitfulness of the devised method, experiments have been accomplished for columns with varying cross-sections; the results of simulations have been compared. The comparison shows good agreement between the present results of finite difference technique with those obtained from the experiments.

Multiclass support vector classification via coding and regression

The multiclass classification problem is considered and resolved through coding and regression. There are various coding schemes for transforming class labels into response scores. An equivalence notion of coding schemes is developed, and the regression approach is adopted for extracting a low-dimensional discriminant feature subspace. This feature subspace can be a linear subspace of the column span of original input data or kernel-mapped feature data. The classification training and prediction are carried out in this feature subspace using a linear classifier, which lead to a simple and computationally light but yet powerful toolkit for classification. Experimental results, including prediction ability and CPU time comparison with LIBSVM, show that the regression-based approach is a competent alternative for the multiclass problem.

First-Order Perturbation Analysis of Singular Vectors in Singular Value Decomposition

Singular value decomposition (SVD) is an important technique in signal processing. In the literature, the perturbation analysis of SVD has been well documented in the context of subspace decomposition. The contribution of the signal subspace to the perturbation of the singular vectors that span the signal subspace is often ignored as it is treated as second and higher order terms, and thus the first-order perturbation is typically given as the column span of the noise subspace. In this correspondence, we show that not only the noise subspace, but also the signal subspace, contribute to the first-order perturbation of the singular vectors. We further show that the contribution of the signal subspace does not impact on the performance analysis of algorithms that rely on the signal subspace for parameter estimation, but it affects the analysis of algorithms that depends on the individual basis vectors. For the latter, we also give a condition under which the contribution of the signal subspace to the perturbation of singular vectors may be ignored in the statistical sense. Numerical examples are provided to validate our theoretic claims.

Design for a large underground space

Large underground spaces are required when constructing multifunctional buildings. These constitute one of the major engineering projects for the World Expo 2010 in Shanghai, China. Restrictions caused by a building’s function, and requirements for arranging municipal pipelines, mean that options for structural systems are limited. This paper presents a scheme design for a large underground space. To achieve a spacious underground passage and to resist the heavy load of the soil that holds pipelines, major structural systems are taken into consideration. Performance criteria for a scheme design involve safety, serviceability and economics. Subsequently, comparisons of a conventional reinforced concrete (RC) system, a prestressed RC system, and a steel–concrete composite (SCC) system are made with regard to these criteria. It is found that a conventional RC structure cannot provide adequate resistance to heavy load at a large column span. Correspondingly, prestressed RC slabs can replace conventional RC structures with the required structural capacity, but suffer drawbacks because construction space is confined. A composite system is desirable for an underground space with a large span and heavy load. Specifically, it has a convenient construction procedure and high economic efficiency which takes advantage of industrial manufacturing of steel members and reduction of concrete formwork.

Separation theorems

Consider a matrix A of order m × n defined on a field F . Let x and y be vectors in the column spans of A and A′ respectively. The vectors x and y are said to be separable if A admits a partition into disjoint matrices of the same order ( A = A 1 ⊕ A 2) such that x belongs to the column span of A 2 and y to that of A′. Additional conditions imposed on A 1 and A 2 reflect stronger shades of separability or of inseparability. For complex matrices, star separability is one such instance. Necessary and sufficient conditions are obtained for separability and star separability of the pair ( x, y). An EP matrix and its transpose (conjugate transpose in the complex case) have the same column span. It is shown that in the class of EP matrices, the separability of the pair ( x, x) for every x in the column span of the matrix characterizes the skew symmetric matrices, and in the class of complex EP matrices, inseparability of similar pairs characterizes the almost definite matrices of Duffin and Morley.