Labour Safety

ОХРАНА ТРУД

Mobility management in multi-tier LiFi networks

Mobility management is an important part of the analysis and design of ultra-dense LiFi networks. This paper presents a two-tier LiFi network and analyses the cross-tier handover rate between the primary and secondary cells. For different conditions of semiangle at half illuminance of the primary and secondary cells, we propose three different coverage models for the secondary cells. Using stochastic geometry, closed-form expressions are derived for the cross-tier handover rate, ping-pong rate and sojourn time in terms of the received optical signal intensity, time-to-trigger and user mobility. The analytical models are validated with simulation results

Generating design-sensitive occupant-related schedules for building performance simulations

Despite the benefits of occupant behavior (OB) models in simulating the effect of design factors on OB, there are challenges associated with their use in the building simulation industry due to extensive time and computational requirements. To this end, we present a novel method to incorporate these models in building performance simulations (BPS) as design-sensitive schedules. Over 2,900 design alternatives of an office were generated by varying orientation, window to wall ratio (WWR), the optical characteristics of windows and blinds, as well as indoor surfaces’ reflectance. By using daylight simulations and stochastic OB modeling, unique light use schedules were generated for each design alternative. A decision tree was then developed to be used by building designers to select light use schedules based on design parameters. These findings are relevant for building energy codes as they provide an approach to incorporate design-sensitive operational schedules for use as BPS inputs by practitioners. These design-sensitive schedules are expected to be superior to default ones currently specified in codes and standards, which ignore the effect of design factors on OB, and ultimately on energy consumption

Dynamics of Adsorbed PMA-d₃ - Effect of Substrate

In the last few years, our group has focused much of our attention on studying the dynamics of polymers adsorbed at interfaces. Much of our work, to date has been on labeled poly(vinyl acetate)-d3 (PVAc-d3)1 and poly(methyl acrylate)-d3 (PMA-d3)2 on silica. We have been able to probe the effects of adsorbed amount,3 molecular mass,4,5 and the effect of overlayer.6 These studies have provided a view of the adsorbed polymer consistent with a motional gradient in the layer with the more mobile segments being those at the air-polymer interface and the less-mobile segments at the substratepolymer interface. However, we have not probed the effect of the interaction with the substrate. In the present work, we describe the dynamics of PMA-d3 adsorbed on different substrates with a focus on how the substrate affects the dynamics of the polymer. In particular, we examine silica- and alumina-based substrates. For silica we explored the behavior of PMA-d3 on Cab-O-Sil silica, both in its native and hydrophobic form. For alumina we have probed the behavior on both alumina powder and also anopore membranes. We find that the dynamics of the adsorbed polymer depends on the nature of the substrate

Exploring occupants\u27 impact at different spatial scales

Buildings\u27 users have widely been accepted as a source of uncertainty in building energy performance predictions. However, it is not evident that the diversity of occupants\u27 presence and behavior at the building level is as important as at the room level. The questions are: How should occupants be modeled at different spatial scales? At the various scales of interest, how much difference does it make if: (1) industry standard assumptions or a dynamic occupant modeling approach is used in a simulation-based analysis, and (2) probabilistic or deterministic models are used for the dynamic modeling of occupants? This paper explores the reliability of building energy predictions and the ability to quantify uncertainty associated with occupant modeling at different scales. To this end, the impacts of occupancy and occupants\u27 use of lighting and window shades on the predicted building lighting energy performance at the room and building level are studied. The simulation results showed that the inter-occupant variation at larger scales is not as important as at the room level. At larger scales (about 100 offices), the rule-base model, custom schedule model, and stochastic lighting use model compared closely for predicting mean annual lighting energy use

Symbol calculus and zeta--function regularized determinants

In this work, we use semigroup integral to evaluate zeta-function regularized determinants. This is especially powerful for non--positive operators such as the Dirac operator. In order to understand fully the quantum effective action one should know not only the potential term but also the leading kinetic term. In this purpose we use the Weyl type of symbol calculus to evaluate the determinant as a derivative expansion. The technique is applied both to a spin--0 bosonic operator and to the Dirac operator coupled to a scalar field.Comment: Added references, some typos corrected, published versio

Linear-scaling techniques for first principles calculations of stationary and dynamic systems

First principles calculations can be a computationally intensive task when studying large systems. Linear-scaling methods must be employed to find the electronic structure of systems consisting of thousands of atoms and greater. The goal of this thesis is to combine the linear-scaling divide-and-conquer (D&C) method with the linear-scaling capabilities of the SIESTA (Spanish Initiative for Electronic Simulations with Thousands of Atoms) density functional theory (DFT) methodology and present this union as a viable approach to large-scale first principles calculations. In particular, the density matrix version of the D&C method is implemented into the SIESTA package. This implementation can accommodate high quality calculations consisting of atom numbers in the tens of thousands using moderate computing resources. Low quality calculations have been tested up to half million atoms using reasonably sized computing resources.The D&C method is extended to better handle atomic dynamics simulations. First, by alleviating issues caused by discontinuities in the potential energy surface, with the application of a switching function on the Hamiltonian and overlap matrices. This allows for a smooth potential energy surface to be generated. The switching function has the additional benefit of accelerating the self-consistent field (SCF) process. Secondly, the D&C frozen density matrix (FDM) is modified to allow for improved charge transfer between the active and constrained regions of the system. This modification is found to reduce both the number of SCF iterations required for self-consistency and the number of relaxation steps in a local geometry optimisation. The D&C paradigm is applied to the real-time approach of time-dependent density functional theory (TDDFT). The method is tested on a linear alkane molecule with varying levels of success.Divergences in the induced dipole moment occur when the external excitation field is aligned parallel to the axis of the molecule. The method succeeds in producing accurate dipole moments when the external field is aligned perpendicular to the molecule. Various techniques are tested to improve the proposed method. Finally, the performance and effectiveness of the current D&C implementation is evaluated by studying three current systems. The first two systems consist of two different DNA sequences and the last system is the large ZIF-100 zeolitic imidazolate framework (ZIF)

System Identification and Control of Front-Steered Ackermann Vehicles through Differentiable Physics

In this paper, we address the problem of system identification and control of a front-steered vehicle which abides by the Ackermann geometry constraints. This problem arises naturally for on-road and off-road vehicles that require reliable system identification and basic feedback controllers for various applications such as lane keeping and way-point navigation. Traditional system identification requires expensive equipment and is time consuming. In this work we explore the use of differentiable physics for system identification and controller design and make the following contributions: i)We develop a differentiable physics simulator (DPS) to provide a method for the system identification of front-steered class of vehicles whose system parameters are learned using a gradient-based method; ii) We provide results for our gradient-based method that exhibit better sample efficiency in comparison to other gradient-free methods; iii) We validate the learned system parameters by implementing a feedback controller to demonstrate stable lane keeping performance on a real front-steered vehicle, the F1TENTH; iv) Further, we provide results exhibiting comparable lane keeping behavior for system parameters learned using our gradient-based method with lane keeping behavior of the actual system parameters of the F1TENTH.Comment: Accepted for IROS 202