Pattern Map Research Articles

Boosted Stacking Ensemble Machine Learning Method for Wafer Map Pattern Classification

Recently, machine learning-based technologies have been developed to automate the classification of wafer map defect patterns during semiconductor manufacturing. The existing approaches used in the wafer map pattern classification include directly learning the image through a convolution neural network and applying the ensemble method after extracting image features. This study aims to classify wafer map defects more effectively and derive robust algorithms even for datasets with insufficient defect patterns. First, the number of defects during the actual process may be limited. Therefore, insufficient data are generated using convolutional auto-encoder (CAE), and the expanded data are verified using the evaluation technique of structural similarity index measure (SSIM). After extracting handcrafted features, a boosted stacking ensemble model that integrates the four base-level classifiers with the extreme gradient boosting classifier as a meta-level classifier is designed and built for training the model based on the expanded data for final prediction. Since the proposed algorithm shows better performance than those of existing ensemble classifiers even for insufficient defect patterns, the results of this study will contribute to improving the product quality and yield of the actual semiconductor manufacturing process.

Deep Hierarchical Pyramid Network With High- Frequency -Aware Differential Architecture for Super-Resolution Mapping

Super-resolution mapping (SRM) is a way to solve the mixed pixel problem in urban land use/land cover caused by the limited spatial-resolving ability of satellite sensors, through resolution enhancement of the classification map. Recently, deep learning based super-resolution mapping (DLSM) networks have been boomed, which can automatically learn a mapping pattern from low-resolution (LR) image to high-resolution (HR) land cover distribution to alleviate mixed pixel problem. However, the urban compositions like buildings, trees and roads, exhibit a multi-scale distribution with different size or orientation, which makes the traditional single-scale DLSM failed for an appropriate recognition. Besides, the urban compositions also show significant spatial heterogeneity with irregular distribution and intricate morphological shape, which are difficult to learn by simple convolutional layer. Therefore, it is necessary to explore the cue of these distribution characteristic to constrain the learning behavior of the network for better detail restoration. In this paper, a super-resolution mapping method based on deep hierarchical pyramid network with high-frequency-aware differential architecture (HiSMNet) is proposed, which establishes a hierarchical pyramid architecture to achieve explicit multi-scale supervision of the feature map, and prompt the network to learn a multi-scale representation. Besides, a differential architecture is designed to enforce the network to intensify the learning of the high-frequency details. The validation experiments demonstrate that HiSMNet achieves superior performances in detail delineation, and outperformed the state-of-the-art DLSM models by up to 10% in terms of overall accuracy.

Numerical study on the hydrodynamics behavior of a central insert microchannel

• A modified 3D model was used to simulate the formation of flow patterns in MC1 and MC2. • The flow pattern graphs captured by the camera agree well with the simulation. • The unique bicontinuous flow patterns in MC2 were obtained and studied. • The size laws of flow patterns in MC1 and MC2 were presented. In this work, the computational fluid dynamics method is used to study the liquid hydrodynamics behavior in the microchannel without central insert (MC1) and the central insert microchannel (MC2), respectively. The maximum deviation between simulation and experiment is 24%. The formations of flow patterns are explained based on contours and force analysis where the flow pattern maps are established by two-phase flow rate. The effects of aqueous phase viscosity and two-phase flow rate on the characteristic sizes of each flow pattern are also explored. Specifically, four unconventional flow patterns are found in MC2, namely the unique droplet flow, the unique slug flow, the unique coarse annular flow and the unique film annular flow. Though the insert occupies part of the channel, the pressure difference in the channel is significantly reduced compared with MC1. Moreover, the insert significantly changes the formation velocity range of each flow pattern, greatly broadens the formation range of annular flow and also has an important influence on the characteristic size of the flow pattern. The organic-phase dimensionless axial size ( L o / W ) and the dimensionless radial size ( D o / W ) of the droplet (slug) are negatively related to the aqueous-phase viscosity ( μ a ) and flow rate ( u a ). The D o / W of the annular is negatively correlated with μ a and positively correlated with organic-phase flow rate ( u o ). This study provides direct numerical evidence that the insert is key to the formation of bicontinuous phase flow pattern, as well as further strengthens our understanding of the flow characteristics and optimization design of insert microchannels.

Universal Gas-Liquid Flow Pattern Map and Its Use on Closure Relationship Selection

Mechanistic modelling is a common approach to predict design parameters such as flow pattern, pressure drop, or liquid holdup in gas-liquid flow in pipes. This approach starts with the application of continuity and momentum balance and required supplementary relationships to close the system of the equations. These additional equations are also called closure relationships which are developed with experimental results for given conditions. These relationships evolved with time as researchers acquired experimental data under different conditions. Unfortunately, new closures are developed for the new conditions rather than universal relationships that can cover a wider set of conditions. This situation generates the need for a methodology that allows the inclusion of newly develop closures to increase the accuracy of the unified mechanistic models. This paper starts with a description of all the available two-dimension maps that can facilitate the visualization of the data. This allows the determination of regions where a particular set of closures minimize the discrepancy between calculated and measured parameters. This paper proposes a simplification of a modern solution to provide a simpler way to visualize the regions corresponding to a set of equations. The final proposed solution reveals a substantial reduction of the average discrepancy of the unified mechanistic model by selecting the most appropriate closures.

The Method for Analyzing the Pitching Motion Pattern of a New Surface Unmanned Wing-sliding Boat

In this paper, a new surface unmanned wing skate (NUSV) is taken as the research object, and the free decay model test under different drafts and different initial pitch angles is completed. In the case of specially selected regular waves, typical swaying tests against waves and waves were carried out. Four mathematical models for system identification of pitch motion modes are established. Based on the system identification theory and the programming idea of the improved genetic algorithm, the NUSV pitch motion mode system identification software is written in C# language. The system identification software is developed based on experimental technology and an analysis method of ship motion patterns is developed based on the optimization theory. This paper completed the following: (1) compared and calculated the mathematical models of system identification based on four-pitch motion modes and determining their motion modes, (2) based on the results of pitch motion mode identification, the predicted values and the test results are in good agreement, which verifies the rationality of the method and the reliability of the self-compiled software, (3) analyzed the variation law of the relative value of each moment that affects the NUSV pitch decay motion with the draft and initial pitch angle, (4) analyzed the influence of the NUSV in the regular wave. The variation law of each moment of the rocking motion with the draught, wave height, and encounter period, and (5) proposed the idea of establishing a rocking motion pattern map based on the rocking test and optimal identification theory. The method and research results proposed in this paper can provide a reliable motion model for the pitch motion control of this type of boat, and provide technical support for its effective regulation of the adverse effect of the pitch on the boat’s stability. It also provides a reference for the seakeeping of this type of boat and the optimization design of the subsequent boat type. The system identification software written can also be used for system identification of the rocking motion mode of this type of unmanned boat in other directions.

A new distributor selection methodology for refrigeration cycles

The pressure gradient analysis is important to be able to observe the homogeneity of the refrigerant and to choose the correct distributor equipment in refrigeration cycles. This research proposes a new method for determining the two-phase pressure gradient accurately compared to existing methods. Two-phase pressure gradient determination approach of Chisholm was modified by integrating the flow pattern map of Thome and Cioncolini. The thermophysical properties of refrigerant 404A were obtained through EES software and the proposed method was coded in the same software. The two-phase pressure gradient results of the proposed method were verified using the experimental data for the refrigerant 404A and compared with the commonly used methods and correlations. It was found that the proposed method predicted the experimental data of R404A better compared to other methods and correlations. The proposed method accurately determines the two-phase pressure drop under superheating and subcooling conditions for various tube wall thicknesses.

FLOW VISUALIZATION AND FLOW PATTERNS IN A FLAT-PLATE POLYPROPYLENE PULSATING HEAT PIPE

The two-phase flow structure in a flat polymeric pulsating heat pipe (PHP) is studied experimentally by high-speed imaging and digital image processing. While flow patterns in tubular pulsating heat pipes can be studied by inserting a short transparent section in a certain position along the channel, in flat PHPs built using transparent plastic sheets one can visualize the entire flow field in the adiabatic region between the evaporator and the condenser. High-speed movies were enhanced by digital image processing to highlight the liquid-vapor interfaces. Different flow patterns were identified, and sorted into a simple flow pattern map.

Mapping the Early Dispersal Patterns of SARS-CoV-2 Omicron BA.4 and BA.5 Subvariants in the Absence of Travel Restrictions and Testing at the Borders in Europe.

The circulation of SARS-CoV-2 omicron BA.4 and BA.5 subvariants with enhanced transmissibility and capacity for immune evasion resulted in a recent pandemic wave that began in April-May of 2022. We performed a statistical phylogeographic study that aimed to define the cross-border transmission patterns of BA.4 and BA.5 at the earliest stages of virus dispersal. Our sample included all BA.4 and BA.5 sequences that were publicly available in the GISAID database through mid-May 2022. Viral dispersal patterns were inferred using maximum likelihood phylogenetic trees with bootstrap support. We identified South Africa as the major source of both BA.4 and BA.5 that migrated to other continents. By contrast, we detected no significant export of these subvariants from Europe. Belgium was identified as a major hub for BA.4 transmission within Europe, while Portugal and Israel were identified as major sources of BA.5. Western and Northern European countries exhibited the highest rates of cross-border transmission, as did several popular tourist destinations in Southern and Central/Western Europe. Our study provides a detailed map of the early dispersal patterns of two highly transmissible SARS-CoV-2 omicron subvariants at a time when there was an overall relaxation of public health measures in Europe.

What are the common uropathogens susceptible antimicrobials for nephrostomy patients?

Introduction: Surgical procedures, such as nephrostomy, prone the patient to postoperative infection. Moreover, multidrug-resistant uropathogens emerge due to the inappropriate use of antibiotics and are now a progressive problem worldwide. Distribution mapping of uropathogens and antimicrobial susceptibility patterns in nephrostomy patients gives urologists a clearer picture to aid in better management of their patients. Objectives: To identify the distribution of uropathogens and antimicrobial susceptibility patterns in nephrostomy patients. Materials & methods: We conducted a retrospective observational review of the medical records, including all adult patients undergoing nephrostomy from 1st January 2020 until 31st December 2021 in a tertiary hospital in Yogyakarta, Indonesia. In each patient with a positive urine culture result, uropathogens and antimicrobial susceptibility test reports were recorded and evaluated separately. Results: Of 100 patients, 76 demonstrated positive urine culture (76%), with 78 isolates from 23 strains. Almost all strains were bacterial (22/23; 95.65%), but one was fungi (1/23; 4.35%). Escherichia coli was the most common uropathogens from the isolates (31/78; 39.74%), followed by Pseudomonas aeruginosa (10/78; 12.82%) and Klebsiella pneumoniae (6/78; 7.69%). Antimicrobial susceptibility tests of 33 antibiotics and 2 antifungals were carried out. Most reports showed susceptibility to Meropenem (11.78%), followed by Gentamicin (10.21%), amikacin (8.12%), and Nitrofurantoin (7.07%). Conclusion: The common uropathogens in nephrostomy patients were Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae. The common susceptible antimicrobials included Meropenem, Gentamicin, amikacin, and Nitrofurantoin.

Associated Patterns in Open-Ended Concept Maps within E-Learning

A concept map is a diagram that visualizes the structure of individual cognitive knowledge. An approach to creating a concept map structure that allows users to contribute concepts and linkages that express their understanding freely is known as an "open-ended concept map." It has been demonstrated that an open-ended concept map accurately depicts student knowledge structures and reveals student differences. However, manually analyzing an open-ended map is difficult, time-consuming, and includes many propositions, especially in a big classroom. Educational data mining could be used to further process and analyze a collection of concept maps. However, many works attempted to employ data mining in order to produce concept maps structure from text documents rather than examining the knowledge representation. This study aimed to identify hidden students' knowledge representation combination patterns using association rules analysis. The dataset used in this study consisted of 27 open-concept maps created by university students. This study found interesting patterns that reveal students' knowledge in understanding the material given by the teacher.

A mechanistic model in annular flow in microchannel tube for predicting heat transfer coefficient and pressure gradient

A mechanistic model that focuses on annular flow is proposed in this work. The new model predicts pressure gradient, void fraction, and heat transfer coefficient in annular flow in a microchannel tube. Six fluids, namely R32, R1234yf, R134a, R1234ze(E), R1233zd(E), and R1336mzz(Z) were tested in previous studies. The tested fluids have a wide range of properties. The results of these six fluids are reviewed and compared to models in the literature. The existing heat transfer models fail to predict the measurements accurately. The proposed model starts from the shear balance at the interface of liquid film and vapor core. The new model uses film thickness to calculate the film Reynolds number. The Film Nusselt number is then calculated. A database approach is adopted to enhance prediction accuracy. Based on the measurements in the database, the model has an MAE of 11.7%, and ME of 0.5% when predicting the heat transfer coefficient. Li and Hrnjak (2022), a flow pattern map based on the same fluids and the same facility, is used to determine the flow pattern. The model is compared to measurements from varied sources in the literature, and it also shows good accuracy. The model can also be extended to other flow patterns in a microchannel evaporator.

Agricultural crop pattern mapping and change analysis at a sub-district level in South-eastern region, Bangladesh using Landsat satellite data from 2010 to 2019

The study first time identified and analyzed winter season agricultural crop patterns (ACP) derived from Land use (LU) maps in between 2010 to 2019 of south-eastern regions of Chittagong, Bangladesh. ACP identification was a challenging task in the worldwide research relevant to crop-related studies. To overcome this, we have considered frequently used traditional unsupervised classifier, such as K-means clustering algorithm technique. This has been applied on 30m pixel Landsat satellite reflectance images to identify crop pattern of the study area using the ENVI 5.3 and ArcGIS 10.8 software’s, respectively. Multiple crops with seven classes were identified with the validation of in-situ ground-truth data and Google Earth (GE) images. The overall accuracy and kappa coefficient values were found at 81.96% and 0.79, respectively. The results suggest a significant variation of crop patterns in the study area and in recent time, the area largely dependent on mixed irrigation approach. Moreover, the crop pattern change was observed in the studied period as mixed crop 19% (9282.17 ha), Lentils (Pelon) 24.80% (11594.38 ha), Melon (Bangi) 22.37% (10461.08 ha), Chilis 17.90% (8367.48 ha), Paddy rice, unused land, and other crops, respectively. Among them, Lentils (Pelon) and Melon (Bangi) are identified as two common crops followed by mixed crops category, cultivated in the winter season as it required less irrigation compared to paddy rice area

Multi-Level Dynamic Analysis of Landscape Patterns of Chinese Megacities during the Period of 2016–2021 Based on a Spatiotemporal Land-Cover Classification Model Using High-Resolution Satellite Imagery: A Case Study of Beijing, China

In today’s accelerating urbanization process, timely and effective monitoring of land-cover dynamics, landscape pattern analysis, and evaluation of built-up urban areas (BUAs) have important research significance and practical value for the sustainable development, planning and management, and ecological protection of cities. High-spatial-resolution remote sensing (HRRS) images have the advantages of high-accuracy Earth observations, covering a large area, and having a short playback period, and they can objectively and accurately provide fine dynamic spatial information about the land cover in urban built-up areas. However, the complexity and comprehensiveness of the urban structure have led to a single-scale analysis method, which makes it difficult to accurately and comprehensively reflect the characteristics of the BUA landscape pattern. Therefore, in this study, a joint evaluation method for an urban land-cover spatiotemporal-mapping chain and multi-scale landscape pattern using high-resolution remote sensing imagery was developed. First, a pixel–object–knowledge model with temporal and spatial classifications was proposed for the spatiotemporal mapping of urban land cover. Based on this, a multi-scale district–BUA–city block–land cover type map of the city was established and a joint multi-scale evaluation index was constructed for the multi-scale dynamic analysis of the urban landscape pattern. The accuracies of the land cover in 2016 and 2021 were 91.9% and 90.4%, respectively, and the kappa coefficients were 0.90 and 0.88, respectively, indicating that the method can provide effective and reliable information for spatial mapping and landscape pattern analysis. In addition, the multi-scale analysis of the urban landscape pattern revealed that, during the period of 2016–2021, Beijing maintained the same high urbanization rate in the inner part of the city, while the outer part of the city kept expanding, which also reflects the validity and comprehensiveness of the analysis method developed in this study.

ANALYSIS THE ENVIRONMENTAL SUPPORT CAPACITY BASED ECOSYSTEM SERVICES TO BASIC DIRECTIONS FOR ADJUSTING THE SPACE PATTERN IN WACO REGENCY

Wajo Regency ecosystem has an abundance of natural and ecological resources with great potential. However, the rapid pace of development activities followed by rapid land conversion has put the sustainability of the supporting ecosystems under pressure. Therefore, it is necessary to map the carrying capacity of the environment based on ecosystem services in Wajo Regency in order to identify the fit between environmental carrying capacity and development in Wajo Regency. Research is at Wajo Regency, through the identification of land cover. ecosystem service-based land capability based analysis is conducted using an Analysis Hierarchy Process to determine the value of ecosystem services from four classes of environmental services, namely water supply, food supply, natural disaster prevention and runoff, and flood management. Instructions for completing spatial patterns in Wajo Regency are performed by analyzing the overlap of the ecosystem service-based bearing capacity map with the Wajo Regency spatial pattern map to obtain a class of spatial pattern alignment. The orientation class is based on the carrying capacity of the land capability based based on ecosystem services to optimize land cover in Wajo Regency. Results of this study show that the land capability based of the four examined ecosystem services in Wajo Regency is dominated by high and low classes. The results of the evaluation of the RTRW by Wajo Regency show that an area of 42,048.97 ha corresponds to the carrying capacity based on ecosystem services. An area of 199,454.11 hectares of land is less oriented, but most of it is retained based on the direction of the spatial pattern. In terms of environmental sustainability based on ecosystem services, the most important land accesses are in the designated settlement areas, other protected areas and local protected areas.

A Multi criteria Decision Making based nonparametric method of fragments to disaggregate daily precipitation

This study addresses the issue of scant availability of sub-daily precipitation data by introducing a novel selection methodology named ‘Pattern Mapping’ (PM) within the existing Method of Fragments (MOF) framework for the disaggregation of daily precipitation. PM introduces multiple statistics based criterion in the selection of fragments thus enhancing accuracy of the selection process. The performance of deterministic and stochastic versions of PM-MOF is compared with three widely used disaggregation methods, namely K Nearest Neighbour based MOF (KNN-MOF), Bartlett-Lewis Rectangular Pulse model (using HYETOS software package) and Micro-Canonical Cascade (MCC) using reanalysis data at 14 global locations spanning various climatic zones. It is seen that the PM-MOF method has considerably lower percentage error in replicating the standard statistics (−50.2 to 50.3% for stochastic PM-MOF and −7.4 to 13.2% for deterministic PM-MOF) when compared to existing methods (KNN-MOF (−65.4 to 76.2%), HYETOS (−78.3 to 69.4%) and MCC (−63.1 to 72%)). The comparison of densities using skill score show that skill score of PM-MOF is 0.97 which is higher than other methods (0.94 for KNN-MOF, 0.83 for HYETOS and 0.85 for MCC). Control experiments designed around varying length of training data and stochastic/deterministic mode (of PM-MOF) ascertain the contribution of the novel methodological improvements in the superior performance of PM-MOF. The robustness of the methodology and geography independent performance of PM-MOF makes it a potent candidate for wider application in hydrological and climate studies.

PEMANFAATAN TEKNOLOGI SISTEM INFORMASI GEOGRAFI UNTUK PEMETAAN POLA ALIRAN AIR TANAH DI KECAMATAN LIMBOTO

Limboto Subdistrict, which is the capital of Gorontalo Regency, has fairly high population growth and is an area that is vulnerable to the effects of drought. This causes the availability of groundwater to decrease. This study aims to utilize the GIS application to determine the pattern of groundwater flow in the Limboto District. This groundwater flow pattern can be used as a reference for further research related to groundwater. The type of data in this study is the type of primary data. The method used in this research is a survey method, namely by measuring directly in the field. The data analysis technique used to determine the pattern of groundwater flow in Limboto Regency is utilizing software (GIS) using ArcGIS 10.7 software to obtain a map of groundwater flow patterns in Limboto District. The results of the spatial analysis of the groundwater flow pattern map in Limboto District show that water flows from the northern part of the study site to the southern part of the study site.

Patterns of Transnational Crime in The Border of Sulawesi Sea - Sulu Sea and Threats to Indonesia’s Maritime

The rise of transnational crime cases in globalization is fatal if countries with maritime areas do not notice it. It is undoubtedly very influential with the threat to the security of the country's territory. Many transnational crime cases arise in the area between the Sulu Sea and the Sulawesi Sea belonging to Indonesia and the Philippines. The case came from these two countries and other countries both in the Region and those not included in the Southeast Asia Region and has confused the maritime area of the Sulu Sea with the Sulawesi Sea. Not only is the threat coming for the Philippines, but the one that has the most impact is the Indonesian defense area because of the emergence of maritime security threats. So, the concept used to find the many patterns of transnational crime cases has emerged using "maritime security" from Christian Bueger. He explained that the understanding of maritime security is disrupting in terms of defense and terms of economic, political, and geo-strategy. From the analysis and mapping of transnational crime patterns in the Sulu Sea - Sulawesi Sea, it is still a threat to Indonesia's maritime security if Indonesia does not strengthen its defense and minimize transnational criminal activities in the Philippines' border sea area and Indonesia. Literature studies and field research are methods used to analyze maritime security themes.

The Playground Shade Index: A New Design Metric for Measuring Shade and Seasonal Ultraviolet Protection Characteristics of Parks and Playgrounds.

Current shading strategies used to protect outdoor playgrounds from harmful solar radiation include the placement of artificial cloth weaves or permanent roofing over a playground site, planting trees in proximity to playground equipment, and using vegetation or surface texture variations to cool playground surfaces. How and where an artificial shade structure is placed or a tree is planted to maximize the shade protection over specific playground areas, requires careful assessment of local seasonal sun exposure patterns. The Playground Shade Index (PSI) is introduced here as a design metric to enable shade and solar ultraviolet exposure patterns to be derived in an outdoor space using conventional aerial views of suburban park maps. The implementation of the PSI is demonstrated by incorporating a machine learning design tool to classify the position of trees from an aerial image, thus enabling the mapping of seasonal shade and ultraviolet exposure patterns within an existing 7180 m2 parkland. This is achieved by modeling the relative position of the sun with respect to nearby buildings, shade structures, and the identified evergreen and deciduous tree species surrounding an outdoor playground.

Developing adiabatic two-phase flow after an expansion valve: Flow development in an 8 mm tube

This paper presents the developing two-phase flow after an expansion valve. R134a with 1.3% POE32 is used as a working medium. The flow patterns are visualized from 15 mm until 595 mm after the expansion valve in a straight tube with an inner diameter of 8 mm. The experiments cover the mass flux from 100 to 480 kg m−2 s−1 and the range of quality from 0.002 to 0.500. The observed flow patterns are classified into four regions as two-phase flow progresses along the tube: well-mixed, separating, separated but developing, and fully developed. Due to the sudden expansion in TEV, the flow structure in the well-mixed region is similar to homogeneous flow, with bubbles or droplets dispersed uniformly. Then, the gravity/buoyancy force becomes more dominant over inertia and surface tension because of the reduction of liquid velocity and the growth of bubbles. Consequently, bubbles migrate upwards while droplets fall downward, characterizing the separating region. After phase separation, the flow characteristics may still change for a certain distance before the flow is fully developed. Based on the observed flow regimes at various working conditions, a 3D flow pattern map is built, adding the distance from the expansion valve as the third dimension besides the mass flux and quality. In a following paper, the authors will discuss the effect of tube diameter, oil, and structure of expansion devices on developing two-phase flow. The developed flow patterns will be compared with the existing flow pattern map in steady conditions as an asymptote.

Microgravity two-phase flow research in the context of vapor compression cycle experiments on parabolic flights

Research on two-phase channel flow in microgravity has extensively investigated flow regimes, pressure drop, and heat transfer during evaporation and condensation processes over several decades. This literature has been primarily motivated by the goal of enabling future space applications for two-phase thermal management systems, among them vapor compression refrigeration cycles. However, relative to the number of two-phase channel flow experiments, research on vapor compression cycles in microgravity has been almost non-existent. This paper reviews two-phase flow research and compares key outcomes with those from system-level measurements obtained from recent testing of a vapor compression cycle at varying inclination angles and on parabolic flights. Previous two-phase channel flow experiments have resulted in several microgravity-specific flow regime maps and have also generally found reduced condensation heat transfer coefficients in microgravity as compared to normal gravity. The flow pattern map of Jayawardena et al. (1997) and generally reduced condensation heat transfer are confirmed by the vapor compression cycle experiments. Regarding evaporation heat transfer coefficients and friction factors, there is not a consensus in the literature on the effects of microgravity in two-phase channel flows. Similarly, the system-level experiments do not show repeatable increases or decreases for those parameters. Lastly, the dependence of system-level behavior on orientation with respect to gravity was tested by performing dynamic inclination experiments, where the inclination angle was changed every 2 min by a 90-degree increment. These tests reveal an increased relative dependence of the vapor compression cycle to orientation with decreasing mass fluxes, in line with two-phase channel flow research that has generally shown that increasing the flow inertia acts to mitigate various flow instabilities and dependence on orientation. However, inclination testing with longer locking times per angle showed a constant relative dependence of the vapor compression cycle to orientation changes.