An Analysis of the Behavior of a Non-Newtonian Fluid in a Flow Reactor

Velocity, temperature and concentration profiles were derived for non-Newtonian laminar flow of a reacting species in a tubular reactor. The equation of motion based on a temperature dependent power-law fluid model and the energy equation with internal heat generation caused by a first order chemical reaction were coupled and solved simultaneously using numerical methods to yield the profiles. The assumptions made in this study were: constant physical properties of the fluid (density, thermal conductivity and heat capacity). fully developed flow, wall temperature and negligible diffusion. Compartmentalized calculations resulted in velocity, temperature and reactant concentration profiles for both the axial and radial directions. The pressure gradient along the reactor was determined from the above equations and the continuity principle. These results should be useful in flow reactor design. The pressure gradients, velocities, temperatures and reactant concentrations are interrelated. Due to the temperature-dependent rheological behavior of the fluid; the axial pressure gradient varied with the temperature in the system. The radial temperature distribution distorted the downstream velocity profiles significantly from the entering profile. The radial temperature profile exhibited a peak located between the reactor wall and centerline. This maximum temperature was explained in terms of the internal heat generation and the relatively low thermal conductivity of the fluid. The extent of chemical reaction depends on the temperature and residence time of the fluid in the reactor. Consequently, the conversion near the reactor centerline was lessened by short residence times and that close to the wall was greater due to longer residence times. The wall temperature had an important effect on the reactant concentration profiles. With a low wall temperature, the reaction near the wall was retarded. Two reactant concentration peaks were observed in contrast to a single maximum at the reactor centerline in the case of a higher wall temperature

Compatibility of convergence algorithms for autonomous mobile robots

We investigate autonomous mobile robots in the Euclidean plane. A robot has a function called target function to decide the destination from the robots' positions, and operates in Look-Compute-Move cycles, i.e., identifies the robots' positions, computes the destination by the target function, and then moves there. Robots may have different target functions. Let $\Phi$ and $\Pi$ be a set of target functions and a problem, respectively. If the robots whose target functions are chosen from $\Phi$ always solve $\Pi$, we say that $\Phi$ is compatible with respect to $\Pi$. If $\Phi$ is compatible with respect to $\Pi$, every target function $\phi \in \Phi$ is an algorithm for $\Pi$ (in the conventional sense). Note that even if both $\phi$ and $\phi'$ are algorithms for $\Pi$, $\{ \phi, \phi' \}$ may not be compatible with respect to $\Pi$. From the view point of compatibility, we investigate the convergence, the fault tolerant ($n,f$)-convergence (FC($f$)), the fault tolerant ($n,f$)-convergence to $f$ points (FC($f$)-PO), the fault tolerant ($n,f$)-convergence to a convex $f$-gon (FC($f$)-CP), and the gathering problems, assuming crash failures. As a result, we see that these problems are classified into three groups: The convergence, the FC(1), the FC(1)-PO, and the FC($f$)-CP compose the first group: Every set of target functions which always shrink the convex hull of a configuration is compatible. The second group is composed of the gathering and the FC($f$)-PO for $f \geq 2$: No set of target functions which always shrink the convex hull of a configuration is compatible. The third group, the FC($f$) for $f \geq 2$, is placed in between. Thus, the FC(1) and the FC(2), the FC(1)-PO and the FC(2)-PO, and the FC(2) and the FC(2)-PO are respectively in different groups, despite that the FC(1) and the FC(1)-PO are in the first group

Minimum algorithm sizes for self-stabilizing gathering and related problems of autonomous mobile robots

We investigate a swarm of autonomous mobile robots in the Euclidean plane. A robot has a function called {\em target function} to determine the destination point from the robots' positions. All robots in the swarm conventionally take the same target function, but there is apparent limitation in problem-solving ability. We allow the robots to take different target functions. The number of different target functions necessary and sufficient to solve a problem $\Pi$ is called the {\em minimum algorithm size} (MAS) for $\Pi$. We establish the MASs for solving the gathering and related problems from {\bf any} initial configuration, i.e., in a {\bf self-stabilizing} manner. We show, for example, for $1 \leq c \leq n$, there is a problem $\Pi_c$ such that the MAS for the $\Pi_c$ is $c$, where $n$ is the size of swarm. The MAS for the gathering problem is 2, and the MAS for the fault tolerant gathering problem is 3, when $1 \leq f (< n)$ robots may crash, but the MAS for the problem of gathering all robot (including faulty ones) at a point is not solvable (even if all robots have distinct target functions), as long as a robot may crash

Experimental Evaluation of Approximation and Heuristic Algorithms for Maximum Distance-Bounded Subgraph Problems

In this paper, we consider two distance-based relaxed variants of the maximum clique problem (Max Clique), named Maxd-Clique and Maxd-Club for positive integers d. Max 1-Clique and Max 1-Club cannot be efficiently approximated within a factor of n1−ε for any real ε>0 unless P=NP , since they are identical to Max Clique (Håstad in Acta Math 182(1):105–142, 1999; Zuckerman in Theory Comput 3:103–128, 2007). In addition, it is NP -hard to approximate Maxd-Clique and Maxd-Club to within a factor of n1/2−ε for any fixed integer d≥2 and any real ε>0 (Asahiro et al. in Approximating maximum diameter-bounded subgraphs. In: Proc of LATIN 2010, Springer, pp 615–626, 2010; Asahiro et al. in Optimal approximation algorithms for maximum distance-bounded subgraph problems. In: Proc of COCOA, Springer, pp 586–600, 2015). As for approximability of Maxd-Clique and Maxd-Club, a polynomial-time algorithm, called ReFindStar d, that achieves an optimal approximation ratio of O(n1/2) for Maxd-Clique and Maxd-Club was designed for any integer d≥2 in Asahiro et al. (2015, Algorithmica 80(6):1834–1856, 2018). Moreover, a simpler algorithm, called ByFindStar d, was proposed and it was shown in Asahiro et al. (2010, 2018) that although the approximation ratio of ByFindStar d is much worse for any odd d≥3, its time complexity is better than ReFindStar d. In this paper, we implement those approximation algorithms and evaluate their quality empirically for random graphs. The experimental results show that (1) ReFindStar d can find larger d-clubs (d-cliques) than ByFindStar d for odd d, (2) the size of d-clubs (d-cliques) output by ByFindStar d is the same as ones by ReFindStar d for even d, and (3) ByFindStar d can find the same size of d-clubs (d-cliques) much faster than ReFindStar d. Furthermore, we propose and implement two new heuristics, Hclub d for Maxd-Club and Hclique d for Maxd-Clique. Then, we present the experimental evaluation of the solution size of ReFindStar d, Hclub d, Hclique d and previously known heuristic algorithms for random graphs and Erdős collaboration graphs

NP-hardness of the sorting buffer problem on the uniform metric

AbstractAn instance of the sorting buffer problem (SBP) consists of a sequence of requests for service, each of which is specified by a point in a metric space, and a sorting buffer which can store up to a limited number of requests and rearrange them. To serve a request, the server needs to visit the point where serving a request p following the service to a request q requires the cost corresponding to the distance d(p,q) between p and q. The objective of SBP is to serve all input requests in a way that minimizes the total distance traveled by the server by reordering the input sequence. In this paper, we focus our attention to the uniform metric, i.e., the distance d(p,q)=1 if p≠q, d(p,q)=0 otherwise, and present the first NP-hardness proof for SBP on the uniform metric

The effect of open green space on the stress level of Bogor Botanical Garden visitors

Stress is a global phenomenon that has become a part of everyday life. Stress can be triggered by the presence of stressors. In Indonesia, the prevalence of psychological stress keeps increasing. This study aims to analyze the perceived restoration effect of green open parks on the stress levels of Bogor Botanical Gardens visitors. A survey of 100 visitors of Bogor Botanical Garden was conducted based on the Perceived Stress Scale. Data on respondent characteristics and stress levels were analyzed using descriptive analysis, the visitor's characteristics that affected their stress levels were analyzed using stepwise linear regression and analysis of variance, and the effect of having a garden and the proximity to open green space on the visitor's stress levels were identified using analysis of variance. The respondents who felt low, medium, and high-stress levels, were 22%, 73%, and 5% respectively. The majority of the respondents perceived Bogor Botanical Garden as restorative. Factors that significantly affect the stress level of respondents are age and purpose of visit. The older the respondent, the lower their stress level tends to be. Visitors who visit for exercise/health activities have significantly lower stress levels than for other visits. In this study, no significant relationship was found between garden ownership and proximity to green parks on the stress level of the respondents

How to collect balls moving in the Euclidean plane

AbstractIn this paper, we study how to collect n balls moving with a fixed constant velocity in the Euclidean plane by k robots moving on straight track-lines through the origin. Since all the balls might not be caught by robots, differently from Moving-target TSP, we consider the following 3 problems in various situations: (i) deciding if k robots can collect all n balls; (ii) maximizing the number of the balls collected by k robots; (iii) minimizing the number of the robots to collect all n balls. The situations considered in this paper contain the cases in which track-lines are given (or not), and track-lines are identical (or not). For all problems and situations, we provide polynomial time algorithms or proofs of intractability, which clarify the tractability–intractability frontier in the ball collecting problems in the Euclidean plane

Separation of Circulating Tokens

Self-stabilizing distributed control is often modeled by token abstractions. A system with a single token may implement mutual exclusion; a system with multiple tokens may ensure that immediate neighbors do not simultaneously enjoy a privilege. For a cyber-physical system, tokens may represent physical objects whose movement is controlled. The problem studied in this paper is to ensure that a synchronous system with m circulating tokens has at least d distance between tokens. This problem is first considered in a ring where d is given whilst m and the ring size n are unknown. The protocol solving this problem can be uniform, with all processes running the same program, or it can be non-uniform, with some processes acting only as token relays. The protocol for this first problem is simple, and can be expressed with Petri net formalism. A second problem is to maximize d when m is given, and n is unknown. For the second problem, the paper presents a non-uniform protocol with a single corrective process.Comment: 22 pages, 7 figures, epsf and pstricks in LaTe

Finding Connected Dense kk-Subgraphs

Given a connected graph $G$ on $n$ vertices and a positive integer $k\le n$, a subgraph of $G$ on $k$ vertices is called a $k$-subgraph in $G$. We design combinatorial approximation algorithms for finding a connected $k$-subgraph in $G$ such that its density is at least a factor $\Omega(\max\{n^{-2/5},k^2/n^2\})$ of the density of the densest $k$-subgraph in $G$ (which is not necessarily connected). These particularly provide the first non-trivial approximations for the densest connected $k$-subgraph problem on general graphs

Approximation Algorithms for the Longest Run Subsequence Problem

We study the approximability of the Longest Run Subsequence problem (LRS for short). For a string S = s_1 ? s_n over an alphabet ?, a run of a symbol ? ? ? in S is a maximal substring of consecutive occurrences of ?. A run subsequence S\u27 of S is a sequence in which every symbol ? ? ? occurs in at most one run. Given a string S, the goal of LRS is to find a longest run subsequence S^* of S such that the length |S^*| is maximized over all the run subsequences of S. It is known that LRS is APX-hard even if each symbol has at most two occurrences in the input string, and that LRS admits a polynomial-time k-approximation algorithm if the number of occurrences of every symbol in the input string is bounded by k. In this paper, we design a polynomial-time (k+1)/2-approximation algorithm for LRS under the k-occurrence constraint on input strings. For the case k = 2, we further improve the approximation ratio from 3/2 to 4/3