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The purpose of this paper is to analyze and compare the performances of novel roadable personal air vehicle (PAV) concepts that meet established operational requirements with different types of engines.

The vehicle configuration was devised considering the dimensions and operational restrictions of the roads, runways and parking lots in South Korea. A folding wing design was adopted for road operations and parking. The propulsion designs considered herein use gasoline, diesel and hybrid architectures for longer-range missions. The sizing point of the roadable PAV that minimizes the wing area was selected, and the rate of climb, ground roll distance, cruise speed and service ceiling requirements were met. For various engine types and mission profiles, the performances of differently sized PAVs were compared with respect to the MTOW, wing area, wing span, thrust-to-weight ratio, wing loading, power-to-weight ratio, brake horsepower and fuel efficiency.

Unlike automobiles, the weight penalty of the hybrid system because of the additional electrical components reduced the fuel efficiency considerably. When the four engine types were compared, matching the total engine system weight, the internal combustion (IC) engine PAVs had better fuel efficiency rates than the hybrid powered PAVs. Finally, a gasoline-powered PAV configuration was selected as the final design because it had the lowest MTOW, despite its slightly worse fuel efficiency compared to that of the diesel-powered engine.

Although an electric aircraft powered only by batteries most capitalizes on the operating cost, noise and emissions benefits of electric propulsion, it also is most hampered by range limitations. Air traffic integration or any safety, and noise issues were not accounted in this study.

Aircraft sizing is a critical aspect of a system-level study because it is a prerequisite for most design and analysis activities, including those related to the internal layout as well as cost and system effectiveness analyses. The results of this study can be implemented to design a PAV.

This study can contribute to the establishment of innovative PAV concepts that can alleviate today’s transportation problems.

This study compared the sizing results of PAVs with hybrid engines with those having IC engines.

This paper examines the political budget cycles in emerging and developing countries using a sample of 91 countries from 1992 to 2019.

This paper employs a pooled ordinary least squares (OLS) model with clustered standard errors at the country level. To address endogeneity issues, the authors also employ a two-step system generalized methods of moments model.

The authors find clear evidence of political budget cycles in emerging and developing countries. The authors consistently find that incumbents increase total government spending, particularly in economic affairs, public services and social welfare, in the year before an election and the election year. In contrast, they contract spending in the year after an election.

Policymakers should be aware of the political budget cycles during election years. Promoting control of corruption and democracy helps to alleviate the effects of the political budget cycles in emerging and developing countries.

The authors are among the first to explore the political budget cycles in emerging and developing countries by focusing on the total government spending and its main compositions, including expenditures on economic affairs, public services and social welfare. Besides, the authors also explore the conditioning effects of control of corruption, political ideology and democracy.

Terrestrial laser scanning (TLS) point clouds have been widely used in deformation measurement for structures. However, reliability and accuracy of resulting deformation estimation strongly depends on quality of each step of a workflow, which are not fully addressed. This study aims to give insight error of these steps, and results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. Thus, the main contributions of the paper are investigating point cloud registration error affecting resulting deformation estimation, identifying an appropriate segmentation method used to extract data points of a deformed surface, investigating a methodology to determine an un-deformed or a reference surface for estimating deformation, and proposing a methodology to minimize the impact of outlier, noisy data and/or mixed pixels on deformation estimation.

In practice, the quality of data point clouds and of surface extraction strongly impacts on resulting deformation estimation based on laser scanning point clouds, which can cause an incorrect decision on the state of the structure if uncertainty is available. In an effort to have more comprehensive insight into those impacts, this study addresses four issues: data errors due to data registration from multiple scanning stations (Issue 1), methods used to extract point clouds of structure surfaces (Issue 2), selection of the reference surface S_ref to measure deformation (Issue 3), and available outlier and/or mixed pixels (Issue 4). This investigation demonstrates through estimating deformation of the bridge abutment, building and an oil storage tank.

The study shows that both random sample consensus (RANSAC) and region growing–based methods [a cell-based/voxel-based region growing (CRG/VRG)] can be extracted data points of surfaces, but RANSAC is only applicable for a primary primitive surface (e.g. a plane in this study) subjected to a small deformation (case study 2 and 3) and cannot eliminate mixed pixels. On another hand, CRG and VRG impose a suitable method applied for deformed, free-form surfaces. In addition, in practice, a reference surface of a structure is mostly not available. The use of a fitting plane based on a point cloud of a current surface would cause unrealistic and inaccurate deformation because outlier data points and data points of damaged areas affect an accuracy of the fitting plane. This study would recommend the use of a reference surface determined based on a design concept/specification. A smoothing method with a spatial interval can be effectively minimize, negative impact of outlier, noisy data and/or mixed pixels on deformation estimation.

Due to difficulty in logistics, an independent measurement cannot be established to assess the deformation accuracy based on TLS data point cloud in the case studies of this research. However, common laser scanners using the time-of-flight or phase-shift principle provide point clouds with accuracy in the order of 1–6 mm, while the point clouds of triangulation scanners have sub-millimetre accuracy.

This study aims to give insight error of these steps, and the results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds.

The results of this study would provide guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. A low-cost method can be applied for deformation analysis of the structure.

Although a large amount of the studies used laser scanning to measure structure deformation in the last two decades, the methods mainly applied were to measure change between two states (or epochs) of the structure surface and focused on quantifying deformation-based TLS point clouds. Those studies proved that a laser scanner could be an alternative unit to acquire spatial information for deformation monitoring. However, there are still challenges in establishing an appropriate procedure to collect a high quality of point clouds and develop methods to interpret the point clouds to obtain reliable and accurate deformation, when uncertainty, including data quality and reference information, is available. Therefore, this study demonstrates the impact of data quality in a term of point cloud registration error, selected methods for extracting point clouds of surfaces, identifying reference information, and available outlier, noisy data and/or mixed pixels on deformation estimation.