Space Efficiency Research Articles

Comparative Analysis of Space Efficiency in Skyscrapers with Prismatic, Tapered, and Free Forms

This study offers a thorough comparative analysis of space efficiency in skyscrapers across three distinct forms: prismatic, tapered, and free. By examining case studies from each form category, this research investigates how architectural and structural design features impact space utilization in supertall towers. The findings reveal form-based differences in space efficiency and design element usage. In prismatic skyscrapers, which are primarily residential and utilize concrete outrigger frames, the average space efficiency was around 72%, with the core occupying 24% of the gross floor area (GFA). Tapered skyscrapers, commonly mixed-use with composite outrigger frames, showed an average space efficiency of over 70%, with a core-to-GFA ratio of 26%. Freeform towers, often mixed-use and using composite outrigger frames, demonstrated a space efficiency of 71%, with an average core-to-GFA ratio of 26%. Despite these variations, a consistent trend emerged: as the height of a building increases, there is a general decline in space efficiency, highlighting the challenges in optimizing space in taller structures. This analysis adds to the understanding of skyscraper design and space utilization, providing important insights for architects and urban planners aiming to improve the efficiency of future high-rise developments.

Assessing the efficiency of urban blue-green space in carbon-saving: Take a high-density urban area in a cold region as an example

Urban blue-green space responds to climate change by providing relatively cooler surrounding environments to indirectly reduce residents' energy consumption and directly adsorb CO2 from the air. However, the carbon-saving potential of urban blue-green space at the urban scale needs to be addressed in the literature. In this study, an improved ideal quantitative model of carbon-saving is constructed from the user's perspective, considering the cooling effects of urban blue-green space and integrating surface temperature, building information, and urban public space layout. A high-density urban area in a northern cold region of China (Tianjin center urban area) is taken as an example to estimate the annual carbon-saving by performing Landsat surface temperature inversions with the delineation of the effective cooling area, as well as regression analyses based on four seasons of data. The results show that the annual carbon-saving in 2021 is about 78 tonneC/km2, equivalent to 2.21 times the carbon sequestration of the same region. Compared with the edge of the center urban area, the urban blue-green space in the center has a carbon-saving with a 1.4 times higher fluctuation value and a cumulative annual difference of about 394 tonneC/km2. Large blue-green patches in the cold region, while capable of conserving more carbon in spring, summer, and fall, become carbon-source in winter due to increased heating energy consumption and reduced willingness of residents to adopt zero-carbon transportation. The indicators that have the most significant impact on the carbon-saving of urban blue-green space are the cooling area and the background surface temperature. The urban blue-green space coverage and the percentage of impervious surfaces, such as buildings and open spaces, will indirectly impact carbon-saving by affecting the cooling area. The above finding recognizes the carbon-saving potential of urban blue-green space in cold regions. It provides a feasible estimation scheme for comparing the carbon-saving capacity in different seasons.

Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology

Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency.

Evaluation of space efficiency criteria in high-rise buildings based on functions: a case study of Türkiye

ABSTRACT High-rise buildings have become a significant solution to address the challenges posed by the rapid growth of urban populations and space limitations in cities. Efficient planning and design of these buildings, aiming to achieve more productivity, can be realized through ensuring space efficiency. This research compares architectural and structural design criteria affecting space efficiency in high-rises based on their functions, aiming to assess the degree of correlation among these criteria, space efficiency, and their interrelations. Currently, no studies examine the differences or similarities in space efficiency of high-rise buildings based on their functions. Additionally, selecting buildings from the same region as samples is a unique aspect of this study. Employing a case study method, the analysis encompasses 42 high-rises in Türkiye, ranging from 100 m to 300 m, and utilizes correlation analysis methods to examine the data. The comprehensive review of space efficiency in high-rises, based on their functions, yielded the following results: (i) Space efficiency ranged from 82.7% to 65.2% in high-rise case studies with different functions, with an average of 73.2%. (ii) A significant majority (83%) of the buildings followed orthogonal designs. (iii) Central core floor planning emerged as the preferred approach. (iv) Increasing elevator density reduced space efficiency. (v) Office buildings favored reinforced concrete frame systems, while residential buildings commonly used reinforced concrete shear wall systems. (vi) As building height increased, elevator and core areas expanded. These findings provide guidance for future high-rise building design and planning.

Trajectory optimization and obstacle avoidance of autonomous robot using Robust and Efficient Rapidly Exploring Random Tree.

One of the key challenges in robotics is the motion planning problem. This paper presents a local trajectory planning and obstacle avoidance strategy based on a novel sampling-based path-finding algorithm designed for autonomous vehicles navigating complex environments. Although sampling-based algorithms have been extensively employed for motion planning, they have notable limitations, such as sluggish convergence rate, significant search time volatility, a vast, dense sample space, and unsmooth search routes. To overcome the limitations, including slow convergence, high computational complexity, and unnecessary search while sampling the whole space, we have proposed the RE-RRT* (Robust and Efficient RRT*) algorithm. This algorithm adapts a new sampling-based path-finding algorithm based on sampling along the displacement from the initial point to the goal point. The sample space is constrained during each stage of the random tree's growth, reducing the number of redundant searches. The RE-RRT* algorithm can converge to a shorter path with fewer iterations. Furthermore, the Choose Parent and Rewire processes are used by RE-RRT* to improve the path in succeeding cycles continuously. Extensive experiments under diverse obstacle settings are performed to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach outperforms existing methods in terms of computational time, sampling space efficiency, speed, and stability.

Exploring the regional cooling efficiency of urban residential vegetation using scenario simulation

The study of the cooling efficiency of vegetation in urban residential areas at a micro-scale is important for improving the thermal environment of those areas. The quantitative analysis of the effect of the layout of different building patterns on the cooling efficiency of green space is particularly crucial. This study takes a typical residential area with a row-column arrangement in Jiangning District, Nanjing City, Jiangsu Province, China, as the research object. Using the ENVI-MET model used for numerical simulation, 15 simulation scenarios were designed based on building orientation, height, and density. The research proposes the methodology of the regional cooling efficiency (RCE) of urban residential vegetation, reveals the daily variation characteristics of the RCE of vegetation in a residential area, and analyzes the factors influencing of regional cooling efficiency. The results showed that the daily variation in RCE for vegetation in the residential area exhibited a single-peak trend. The minimum and maximum RCE values appeared at 6:00 and 14:00, respectively. The average air temperature and building density in the residential area had a significant positive correlation with RCE, while average relative humidity had a negative correlation. Average wind speed, average building height, and average sky view factor showed nonlinear correlations with RCE, and the importance ranking of each factor's effect on RCE was air temperature > relative humidity > building density > wind speed > building height > sky view factor. This study will provide theoretical support for improving the thermal environment in urban residential areas during the urban planning process.

Does Introducing FAQs Boost Self-Service Government?—A Study of Local Government Websites

ABSTRACT Government websites remain a crucial means of communication with citizens, even in times of artificial intelligence. However, if not designed with usability in mind, users will call or e-mail to get answers, thereby wasting administrative resources. Little research exists on this issue of government efficiency. Drawing on self-efficacy theory, we address this gap and introduce Frequently Asked Questions (FAQs) to the websites of five Swiss local governments to see if self-service government increases. We find improvements only if administrations tell users about the FAQs on other channels. Thus, our study advances the debate on government efficiency in the digital space.

Optimization of ventilation efficiency in tunnel-type underground spaces using response surface methodology: a case study of Yunlong Mountain civil defense in Xuzhou

Civil defense projects, designed as wartime underground spaces, often lack effective natural ventilation and have considerable depth, which complicates their use as public spaces in peacetime. However, the application of passive ventilation technologies can create effective airflow channels within these structures, significantly enhancing ventilation efficiency and thus improving the overall thermal comfort level. For this study, air age, along with average wind speed, temperature, and relative humidity as stipulated by the “Requirements for Environmental Sanitation of Civil Air Defense Works during Peacetime Use” (GBT 17216-2012), were selected as evaluation metrics. This paper compares the ventilation effectiveness between single ventilation shafts and multiple ventilation shafts under positive and negative pressure conditions in underground civil defense structures. The results indicate that negative pressure ventilation in multiple shaft configurations performs optimally across various ventilation approaches. Subsequently, the Response Surface Methodology (RSM) was utilized to further optimize the positioning of multiple ventilation shafts. The study examined the impact of three ventilation shaft locations on average wind speed, temperature, relative humidity, and air age, leading to an optimized design. Specifically, the optimal positions are 54.76 m for Shaft A, 51.45 m for Shaft B, and 79.85 m for Shaft C, achieving an average wind speed of 0.222 m/s, a temperature of 26 °C, a relative humidity reduction to 85.47%, and an average air age of 10.57 s. This research provides practical insights for the optimization of ventilation in underground civil defense facilities.

TeST: Temporal-spatial separated transformer for temporal action localization

Temporal action localization is a fundamental task in video understanding. Existing methods fall into three categories: anchor-based, actionness-guided, and anchor-free. Anchor-based and actionness-guided models need huge computation resources to process redundant proposals or enumerate every possible proposal. Anchor-free models with lighter parameters become a more attractive option as temporal actions become more complex. However, they typically struggle to achieve high performance due to the need to aggregate global temporal-spatial features at every time step. To overcome this limitation, we design three efficient transformer-based architectures, bringing two advantages: (i) the global receptive field of transformers enables models to aggregate spatial and temporal at each time step, and (ii) the transformers could capture the moment-level feature, enhancing localization performance. Our designed architectures are adapted to any framework, thus we propose a simple but effective anchor-free framework named TeST. Compared to strong baselines, TeST achieves 0.96% to 3.20% improvement on two real-world datasets. Meanwhile, it improves time efficiency by 1.36 times and space efficiency by 1.08 times. Further experiments prove the effectiveness of TeST’s modules. Implementation of our work is available at https://github.com/whr000001/TeST.

Efficient Daylighting: The Importance of Glazing Transmittance and Room Surface Reflectance

This study quantitatively analyzes the influence of the spectral characteristics, reflectance or transmittance, of different materials on the lighting of an interior space with natural and artificial light. For this purpose, a three-dimensional simulated classroom is used, where each of the components is assigned specific materials with an associated reflectance or transmittance. Additionally, two types of lighting are available: 6500 K daylight and light from six continuous spectrum LED luminaires. The lighting is evaluated on two planes: the work plane and the corneal plane (80 cm and 120 cm from the floor, respectively). Three versions of the same classroom were analyzed by varying the walls (white, blue, and red), each with a different neutral-colored floor. Furthermore, calculations were performed in each situation considering two different types of glazing in the windows, with 20% and 88% transmittance. The photopic and melanopic lighting analysis was carried out with the ALFA calculation program to verify the necessary requirements for adequate lighting. The results show that the white classroom is the best lit, followed by the blue and finally the red, due to the reflectance characteristics of the walls and floor although slight differences among them are found. It was found that in some cases, additional auxiliary luminaires would be required for proper lighting depending on the transmittance of the glazing. This study highlights the critical role of material selection in optimizing both photopic and melanopic lighting, with practical implications for energy efficiency and occupant well-being in educational spaces.

Upscaling cargo bike sharing in cities: A comparative case study

Urban mobility transitions are essential to mitigate climate change and improve the quality of life in cities. Cargo bikes (CBs) show promise in replacing motorised vehicles due to their lower carbon intensity, space efficiency, and ability to reduce air and noise pollution. CB sharing relieves users from purchase and maintenance costs. However, it is mainly adopted by individuals with high environmental awareness. Barriers to CB sharing stem from the urban infrastructure, individual mobility choices, and the design of CB sharing organisations (CBSOs). This article analyses upscaling pathways for CB sharing, i.e., increasing their use by a broader audience and reshaping the urban mobility regime. It delivers a comparative case study analysis of two CBSOs: Grätzlrad, Vienna, and LastenVelo e.V., Freiburg. Data was collected through academic and grey literature review and 15 semi-structured interviews with CB sharing stakeholders and experts. The analytical framework is informed by strategic niche management, viewing CB sharing as a niche innovation in the urban mobility regime. The article enhances understanding of CB sharing, the interaction of CBSOs with key actors, and their scalability. CBSOs should increase the availability of shared CBs while reducing the organisational effort required from users. New ways of CB sharing, e.g., integration in shared mobility hubs, should be explored. Municipal actors play a crucial role in upscaling and ensuring that CB sharing reaches a diverse user base. The findings are useful for academia, practitioners and policymakers working with CB sharing and other sustainable urban mobility solutions.

Constrained large-scale multiobjective optimization based on a competitive and cooperative swarm optimizer

Many engineering application problems can be modeled as constrained multiobjective optimization problems (CMOPs), which have attracted much attention. In solving CMOPs, existing algorithms encounter difficulties in balancing conflicting objectives and constraints. Worse still, the performance of the algorithms deteriorates drastically when the size of the decision variables scales up. To address these issues, this study proposes a competitive and cooperative swarm optimizer for large-scale CMOPs. To balance conflict objectives and constraints, a bidirectional search mechanism based on competitive and cooperative swarms is designed. It involves two swarms, approximating the true Pareto front from two directions. To enhance the search efficiency in large-scale space, we propose a fast-converging competitive swarm optimizer. Unlike existing competitive swarm optimizers, the proposed optimizer updates the velocity and position of all particles at each iteration. Additionally, to reduce the search range of the decision space, a fuzzy decision variables operator is used. Comparison experiments have been performed on test instances with 100–1000 decision variables. Experiments demonstrate the superior performance of the proposed algorithm over five peer algorithms.

Space Efficiency of Tall Buildings in Singapore

Space efficiency in Singaporean tall buildings results from a complex interplay of historical, architectural, engineering, technological, socioeconomic, and environmental factors. The city-state’s innovative and adaptive approach has enabled it to overcome the challenges associated with skyscraper construction, leading to the development of some of the most advanced and sustainable high-rise structures in the world. However, there is currently a lack of detailed analysis on space utilization in Singaporean high-rise buildings. This study addresses this gap by examining 63 cases. The main findings of this research: 1. Residential functions, central core layouts, and prismatic shapes are the most frequent. 2. Concrete material with a shear-walled frame system is the preferred structural choice. 3. Average spatial efficiency is 80%, and the core-to-GFA (Gross Floor Area) ratio averages 17%. These metrics vary from a minimum of 68% and 5% to a maximum of 91% and 32%, respectively. These insights offer valuable guidance for Singaporean construction professionals, particularly architects, helping them make informed design decisions for high-rise projects.

Proton-gated organic thin-film transistors for leaky integrate-and-fire convolutional spiking neural networks

Artificial spiking neurons, integral to the functionality of spiking neural networks, are designed to mimic the information transmission via discrete spikes in biological nervous systems. Traditional approaches that necessitate the charging of capacitors and the inclusion of discharge circuits for neuron membrane potential integration and leakage, present challenges in terms of cost and space efficiency. To overcome the challenges, this work proposes a hardware leaky integrate-and-fire neuron based on organic thin-film transistors. Under the electric field, the ion dynamics in the gate electrolyte can mimic the processes of membrane potential integration, leakage, and reset in spiking neurons. The convolutional spiking neural networks composed of such organic spiking neurons achieves excellent recognition rates (∼97.26 %) on the MNIST dataset. This indicates that the organic spiking neuron has enormous potential in next-generation non-von Neumann neuromorphic computing.

Symmetric engineered central cross-shaped broadband metamaterial absorber with high absorption and stability for solar sailing and solar energy applications

We propose a theoretical design and analysis of a broadband metamaterial absorber (MMA) with significant potential for solar sailing applications which is a method of spacecraft propulsion that usages the momentum of sunlight to propel a spacecraft through space. The absorber features a metal-dielectric-metal configuration with a tungsten (W) based resonator and ground plane, and a Silicon-dioxide (SiO₂) substrate. Addressing the critical need for materials that can efficiently harness solar radiation for propulsion in space, our design achieves an average absorption of 99.15 % over a broad spectrum from 250 nm to 1200 nm, covering the UV–Visible–NIR regions, with near-unity absorption peaks at 362 nm and 915.8 nm. It maintains high absorptions of 84.9 % and 86 % under transvers electric and transvers magnetic modes respectively, demonstrating excellent wide incident angle stability and polarization insensitivity due to its symmetric design. PCR values close to zero confirm its functionality as an absorber rather than a polarizer. The MMA shows minimal deformation across temperatures from 500 K to 1750 K and remains stable under various mechanical stresses, proving its durability and efficiency in space. Additionally, in solar thermophotovoltaic (STPV) systems, the MMA demonstrates high photothermal conversion efficiency (PTCE) over a wide temperature range (500 °C to 1500 °C) and different concentration factors. This dual functionality highlights its potential for both efficient space exploration and terrestrial solar energy harvesting, making it a versatile tool for future technological applications.

Linear symmetric self-selecting 14-bit kinetic molecular memristors.

Artificial Intelligence (AI) is the domain of large resource-intensive data centres that limit access to a small community of developers1,2. Neuromorphic hardware promises greatly improved space and energy efficiency for AI but is presently only capable of low-accuracy operations, such as inferencing in neural networks3-5. Core computing tasks of signal processing, neural network training and natural language processing demand far higher computing resolution, beyond that of individual neuromorphic circuit elements6-8. Here we introduce an analog molecular memristor based on a Ru-complex of an azo-aromatic ligand with 14-bit resolution. Precise kinetic control over a transition between two thermodynamically stable molecular electronic states facilitates 16,520 distinct analog conductance levels, which can be linearly and symmetrically updated or written individually in one time step, substantially simplifying the weight update procedure over existing neuromorphic platforms3. The circuit elements are unidirectional, facilitating a selector-less 64 × 64 crossbar-based dot-product engine that enables vector-matrix multiplication, including Fourier transform, in a single time step. We achieved more than 73 dB signal-to-noise-ratio, four orders of magnitude improvement over the state-of-the-art methods9-11, while consuming 460× less energy than digital computers12,13. Accelerators leveraging these molecular crossbars could transform neuromorphic computing, extending it beyond niche applications and augmenting the core of digital electronics from the cloud to the edge12,13.

Semi-Empirical Model Based on the Influence of Turbulence Intensity on the Wake of Vertical Axis Turbines

In the context of energy shortages and the development of new energy sources, tidal current energy has emerged as a promising alternative. It is typically harnessed by deploying arrays of multiple water turbines offshore. Vertical axis water turbines (VAWTs), as key units in these arrays, have wake effects that influence array spacing and energy efficiency. However, existing studies on wake velocity distribution models for VAWTs are limited in number, accuracy, and consideration of influencing factors. A precise theoretical model (Lam’s formula) for wake lateral velocity can better predict wake decay, aiding in the optimization of tidal current energy array designs. Turbulence in the ocean, serving as a medium for energy exchange between high-energy and low-energy water flows, significantly impacts the wake recovery of water turbines. To simplify the problem, this study uses software ANSYS Fluent 2020 R2 for two-dimensional simulations of VAWT wake decay under different turbulence intensities, confirming the critical role of turbulence intensity in wake velocity decay. Based on the obtained data, a new mathematical approach was employed to incorporate turbulence intensity into Lam’s wake formula for VAWTs, improving its predictive accuracy with a minimum error of 1%, and refining some parameter calculations. The results show that this model effectively reflects the impact of turbulence on VAWT wake recovery and can be used to predict wake decay under various turbulence conditions, providing a theoretical basis for VAWT design, optimization, and array layout.

Deciphering the effects of 2D/3D urban morphology on diurnal cooling efficiency of urban green space

Urban green spaces (UGS) have emerged as a main nature-based solution proven to effectively cool urban areas, and cooling efficiency (CE) serves as a prominent indicator for assessing the performance of UGS. Yet few studies have explored the diurnal dynamics of CE and the comprehensive effects of both 2D and 3D urban morphology on CE over a 24-h period. In this study, we employed diurnal land surface temperature (LST) data from Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to delve into the diurnal CE of UGS within the urban core area of megacity Paris, France. Meanwhile, using high-resolution land cover data, digital height model, and explainable machine learning models, we elucidated the intricate relationship between various 2D and 3D urban morphology metrics and CE during a 24-h cycle. In summary, city-scale continuous monitoring revealed diurnal CE variations, with values ranging from 0.008 °C to 0.13 °C and a standard deviation of 0.04 °C. On an average of a day, the relative importance of the 2D and 3D urban form indicators was 77.25 % and 22.75 %, respectively. Enhancing the dispersion of trees or improving the integrity of non-tree vegetation patches proves to be an effective strategy for augmenting CE. The results can be further used in urban planning to improve urban thermal resilience and adaptability.

Urban Transformation: Opportunities for Land Use Change in Urban Fabric Redevelopment

With the arrival of modernity in Iran, the concept of the "city" as we understand it today was born, undergoing significant transformations that have continued to evolve over time. These transformations in the physical structure of the city have created multifaceted challenges in three primary dimensions: housing, urban facilities, and transportation. This research, adopting a thematic approach to these challenges and aiming to provide valuable insights for social policymakers and urban planners, employs a descriptive-analytical method. It leverages existing data from documentary resources to explore opportunities for land use change in the process of redeveloping urban fabrics. The study delves deeply into the role of urban transformation in enhancing the quality of life and improving the efficiency of urban spaces. By investigating urban fabrics as crucial components in the redevelopment process, the research analyzes the various factors influencing land use change. Through detailed case studies, the article identifies existing opportunities for the improvement and modification of land uses within urban fabrics, offering practical solutions for optimizing these processes. The ultimate goal of this study is to propose comprehensive strategies for the optimal utilization of urban resources, thereby significantly enhancing the quality of life in urban environments. This study aims to provide a thorough understanding of the dynamics at play in urban redevelopment and to offer actionable recommendations for policymakers and urban planners to create more livable, efficient, and sustainable urban spaces.

Isogeometric modeling and vibro-acoustic analysis of flow-excited irregular cavity-plate-exterior space coupled system

The flow-induced noise has become an important noise source in marine sonar self-noise, which can adversely affect the normal operation of sonar. The marine sonar cabin is simplified as a cavity-plate-exterior space coupled system whose flow-induced vibro-acoustic characteristics are investigated in this paper. An isogeometric vibro-acoustic formulation is proposed in which the cavity with an irregular geometry is precisely described by adjusting the control points and corresponding weights. The flow-induced vibro-acoustic response is obtained by transferring the turbulent pressure data from computational fluid dynamics into the isogeometric vibro-acoustic model. Imposing turbulent pressure into the isogeometric control points is proposed to achieve this objective using a node-based interpolation method. The vibro-acoustic modeling is validated and compared with previous experimental results. These comparisons demonstrate that the developed formulation accurately predicts the vibro-acoustic characteristics of the fluid-excited coupled system. The influences of flow speed, acoustic medium, and cavity shape on flow-excited vibration and sound radiation are discussed. Results show a decrease in radiated acoustic power and radiation efficiency in the exterior space, and a shift in the plate-exterior space coupling modal frequency to lower frequencies when the cavity changes from convex to concave.