Pattern Speed Research Articles

A mechanism of bar formation in disc galaxies: Synchronization of apsidal precession

ABSTRACT We discuss the mechanism(s) of bar formation in isolated and tidally interacting disc galaxies using the results of idealized collision-less N-body simulations of the galaxies. In order to better understand the mechanism, we investigate orbital eccentricities (e), epochs of apocentre passages (ta), azimuthal angles at ta (φa), precession rates (Ωpre), for individual stars, as well as bar strengths represented by relative m = 2 Fourier amplitude (A2) and bar pattern speeds (Ωbar). The main results are as follows. A significant fraction of stars with initially different φa and Ωpre in an isolated disc galaxy can have similar values within several dynamical time-scales. This synchronization of φa and Ωpre, which is referred to as apsidal precession synchronization (‘APS’) in this study, is caused by the enhanced strength of the tangential component of gravitational force. A weak seed bar (A2 < 0.1) is first formed through APS in local regions of a disc, then the bar grows due to APS. In the bar growth phase (0.1 < A2 < 0.4), APS can proceed more efficiently due to stronger tangential force from the bar so that it can enhance the bar strength further. This positive feedback loop in APS is the key physical mechanism of bar growth in isolated stellar discs. Bar formation can be severely suppressed in discs with lower disc mass fractions and/or higher Q parameters due to much less efficient APS. APS proceeds more rapidly and more efficiently due to strong tidal perturbation in the formation of tidal bars compared to spontaneous bar formation.

SDSS IV MaNGA: bar pattern speed in Milky Way analogue galaxies

ABSTRACT Most secular effects produced by stellar bars strongly depend on the pattern speed. Unfortunately, it is also the most difficult observational parameter to estimate. In this work, we measured the bar pattern speed of 97 Milky-Way analogue galaxies from the MaNGA survey using the Tremaine–Weinberg method. The sample was selected by constraining the stellar mass and morphological type. We improve our measurements by weighting three independent estimates of the disc position angle. To recover the disc rotation curve, we fit a kinematic model to the H α velocity maps correcting for the non-circular motions produced by the bar. The complete sample has a smooth distribution of the bar pattern speed ($\Omega _{\rm Bar}=28.14^{+12.30}_{-9.55}$ km s−1 kpc −1), corotation radius ($R_{CR} = 7.82^{+3.99}_{-2.96}$ kpc), and the rotation rate ($\mathcal {R} = 1.35^{+0.60}_{-0.40}$). We found two sets of correlations: (i) between the bar pattern speed, the bar length and the logarithmic stellar mass (ii) between the bar pattern speed, the disc circular velocity and the bar rotation rate. If we constrain our sample by inclination within 30° < i < 60° and relative orientation 20° < |PAdisc − PAbar| < 70°, the correlations become stronger and the fraction of ultra-fast bars is reduced from 20 to 10 per cent of the sample. This suggests that a significant fraction of ultra-fast bars in our sample could be associated with the geometric limitations of the TW method. By further constraining the bar size and disc circular velocity, we obtain a subsample of 25 Milky-Way analogues galaxies with distributions $\Omega _{\rm Bar}=30.48^{+10.94}_{-6.57}$ km s−1 kpc−1, $R_{\rm CR} = 6.77^{+2.32}_{-1.91}$ kpc, and $\mathcal {R} = 1.45^{+0.57}_{-0.43}$, in good agreement with the current estimations for our Galaxy.

Integrating CFD-GIS modelling to refine urban heat and thermal comfort assessment

Constant urban growth exacerbates the demand for residential, commercial and traffic areas, leading to progressive surface sealing and urban densification. With climate change altering precipitation and temperature patterns worldwide, cities are exposed to multiple risks, demanding holistic and anticipatory urban planning strategies and adaptive measures that are multi-beneficial. Sustainable urban planning requires comprehensive tools that account for different aspects and boundary conditions and are capable of mapping and assessing crucial processes of land-atmosphere interactions and the impacts of adaptation measures on the urban climate system. Here, we combine Computational Fluid Dynamics (CFD) and Geographic Information System (GIS) capabilities to refine an existing 2D urban micro- and bioclimatic modelling approach. In particular, we account for the vertical and horizontal variability in wind speed and air temperature patterns in the urban canopy layer. Our results highlight the importance of variability of these patterns in analysing urban heat development, intensity and thermal comfort at multiple heights from the ground surface. Neglecting vertical and horizontal variability, non-integrated CFD modelling underestimates mean land surface temperature by 7.8 °C and the Universal Thermal Climate Index by 6.9 °C compared to CFD-integrated modelling. Due to the strong implications of wind and air temperature patterns on the relationship between surface temperature and human thermal comfort, we urge caution when relying on studies solely based on surface temperatures for urban heat assessment and hot spot analysis as this could lead to misinterpretations of hot and cool spots in cities and, thus, mask the anticipated effects of adaptation measures. The integrated CFD-GIS modelling approach, which we demonstrate, improves urban climate studies and supports more comprehensive assessments of urban heat and human thermal comfort to sustainably develop resilient cities.

Integration of velocity-dependent spatio-temporal structure of place cell activation during navigation in a reservoir model of prefrontal cortex.

Sequential behavior unfolds both in space and in time. The same spatial trajectory can be realized in different manners in the same overall time by changing instantaneous speeds. The current research investigates how speed profiles might be given behavioral significance and how cortical networks might encode this information. We first demonstrate that rats can associate different speed patterns on the same trajectory with distinct behavioral choices. In this novel experimental paradigm, rats follow a small baited robot in a large megaspace environment where the rat's speed is precisely controlled by the robot's speed. Based on this proof of concept and research showing that recurrent reservoir networks are ideal for representing spatio-temporal structures, we then test reservoir networks in simulated navigation contexts and demonstrate they can discriminate between traversals of the same path with identical durations but different speed profiles. We then test the networks in an embodied robotic setup, where we use place cell representations from physically navigating robots as input and again successfully discriminate between traversals. To demonstrate that this capability is inherent to recurrent networks, we compared the model against simple linear integrators. Interestingly, although the linear integrators could also perform the speed profile discrimination, a clear difference emerged when examining information coding in both models. Reservoir neurons displayed a form of statistical mixed selectivity as a complex interaction between spatial location and speed that was not as abundant in the linear integrators. This mixed selectivity is characteristic of cortex and reservoirs and allows us to generate specific predictions about the neural activity that will be recorded in rat cortex in future experiments.

The influence of surface and speed on biomechanical external loads obtained from wearable devices in rearfoot strike runners

ABSTRACT External load variables such as peak tibial acceleration (PTA), peak vertical ground reaction forces (GRF) and its instantaneous vertical loading rate (IVLR) may contribute to running injuries although evidence is conflicting given the influence of training load and tissue health on injuries. These variables are influenced by footwear, speed, surface and foot strike pattern during running. The purpose of this study was to assess the influence of four surfaces and two running speeds on external load variables in rearfoot strike (RFS) runners. Twelve RFS runners (confirmed with sagittal foot contact angle) completed a 2-min running bout on a treadmill and 50-m running bouts over the three surfaces (pavement, rubber track and grass) in standardised shoes at their preferred speed and 20% faster. PTA and vertical GRFs were collected using inertial measurement units and in-shoe force insoles. No interaction or surface effects were observed (p > 0.017). The faster speed produced greater axial PTA (+19.2%; p < 0.001), resultant PTA (+20.7%; p < 0.001), peak vertical GRF (+6.6%; p = 0.002) and IVLR (+16.5%; p < 0.001). These findings suggest that surface type does not influence PTA, peak vertical GRF and IVLR but that running faster increases the magnitude of these external loads regardless of surface type in RFS runners.

Automated Identification of “Dunkelflaute” Events: A Convolutional Neural Network–Based Autoencoder Approach

Abstract As wind and solar power play increasingly important roles in the European energy system, unfavorable weather conditions, such as “Dunkelflaute” (extended calm and cloudy periods), will pose ever greater challenges to transmission system operators. Thus, accurate identification and characterization of such events from open data streams (e.g., reanalysis, numerical weather prediction, and climate projection) are going to be crucial. In this study, we propose a two-step, unsupervised deep learning framework [wind and solar network (WISRnet)] to automatically encode spatial patterns of wind speed and insolation, and subsequently, identify Dunkelflaute periods from the encoded patterns. Specifically, a deep convolutional neural network (CNN)–based autoencoder (AE) is first employed for feature extraction from the spatial patterns. These two-dimensional CNN-AE patterns encapsulate both amplitude and spatial information in a parsimonious way. In the second step of the WISRnet framework, a variant of the well-known k-means algorithm is used to divide the CNN-AE patterns in region-dependent meteorological clusters. For the validation of the WISRnet framework, aggregated wind and solar power production data from Belgium are used. Using a simple criterion from published literature, all the Dunkelflaute periods are directly identified from this 6-year-long dataset. Next, each of these periods is associated with a WISRnet-derived cluster. Interestingly, we find that the majority of these Dunkelflaute periods are part of only 5 clusters (out of 25). We show that in lieu of proprietary power production data, the WISRnet framework can identify Dunkelflaute periods from public-domain meteorological data. To further demonstrate the prowess of this framework, it is deployed to identify and characterize Dunkelflaute events in Denmark, Sweden, and the United Kingdom.

Heterogeneous warming impacts of desert wind farms on land surface temperature and their potential drivers in Northern China

To address rapid climate change, wind energy has been widely developed in China in the last two decades. However, wind farm (WF) turbulence effects can change the local climate by redistributing temperature, humidity, and heat fluxes. Previous studies indicate that WFs can significantly increase nighttime land surface temperature (LST); however, their conclusions are mainly derived from individual WFs and ignore heterogeneous impacts among multi-WFs in China. Another large source of uncertainty is that the WFs used in previous studies are mainly located in croplands or grasslands, which may obscure direct WF impacts because of the interactions between vegetation and the atmosphere. In this study, we detect impacts with MODIS LST products during 2001–2018 at sixteen WFs in the desert of northern China. The results suggest that the averaged warming impacts of WFs on LST are similar between nighttime (0.237 °C) and daytime (0.250 °C). However, the uncertainty is much greater for daytime (SD = 0.519 °C) than for nighttime (SD = 0.146 °C) due to spatially heterogeneous impacts of desert WFs on LST. Optimal structural equation models suggest that wind speed, precipitation, and distribution patterns of wind turbines mainly explain the spatial heterogeneity of the desert WF impacts on nighttime LST. Given the rapid development of WFs globally, the local warming impacts of WFs and their corresponding mechanisms should be highlighted as a high priority in the fields of energy and climate.

Wind Generator Output Power Smoothing by Using Pitch Controller

It is well known that pitch controller can maintain output power of wind generator at rated level when wind speed is above the rated speed. Moreover, it can also enhance the transient stability of wind generator when severe network disturbance occurs in power system. In this paper, another new feature of pitch controller is analyzed. As wind speed varies randomly the output power of wind generator fluctuates continuously. This fluctuation can be minimized significantly by changing the blade pitch angle of wind turbine. Our proposed pitch controller can do this well. The wind generator output power loss and smoothness level are analyzed when the proposed pitch controller is used with wind turbine. Comparative studies are carried on using three types of input command power of the controller. Some technical points of mechanical servo system of wind turbine are emphasized to reduce the load of wind turbine. Moreover, different types of wind speed patterns are used to validate the effectiveness of the proposed controller. Simulation results show that the wind power fluctuation can be reduced significantly by using the proposed fuzzy logic based pitch controller.

The pattern speeds of vertical breathing waves

ABSTRACT We measure and compare the pattern speeds of vertical breathing, vertical bending, and spiral density waves in two isolated N-body+SPH simulations, using windowed Fourier transforms over $1 \mbox{$\:{\rm Gyr}$}$ time intervals. We show that the pattern speeds of the breathing waves match those of the spirals but are different from those of the bending waves. We also observe matching pattern speeds between the bar and breathing waves. Our results not only strengthen the case that, throughout the disc, breathing motions are driven by spirals but indeed that the breathing motions are part and parcel of the spirals.

Particle Number and Size Distributions (PNSD) from a Hybrid Electric Vehicle (HEV) over Laboratory and Real Driving Emission Tests

Particle number (PN) emissions from hybrid electric vehicles (HEV) during engine ignition and re-ignition events are an important but scarcely reported area. The objectives of the present work are to study the effects of drive cycle properties on the engine behaviour of a hybrid electric vehicle (HEV) and to investigate how this impacts the tailpipe PN emissions and their size distributions (PNSD). Worldwide harmonised light vehicles test cycle (WLTC) testing was conducted, as well as chassis dynamometer emission measurements over a realistic real driving emissions (RDE) speed pattern, using a Euro 5 Toyota Prius HEV with a Cambustion DMS500 sampling PN concentrations at the tailpipe. It is shown that the number of vehicle stops during a test cycle has a direct impact on the re-ignition activity for the HEV. 64 ± 3% of the total PN from WLTC testing was produced during engine re-ignition events while only 6 ± 1% was from stabilised engine operation. Similar proportions were observed for the RDE-style test cycle. The majority of engine reignition and destabilised activity, and hence PN emission, was during the low-speed sections of the drive cycles used. The average PNSD across cycle phases was different between cycles, due to the influence of dynamic properties on engine behaviour and hence the PN emission profile. The PNSD at the engine re-ignition and destabilised events had a merged wide peak with a maximum at 60 nm diameter and a shoulder at 12 nm diameter. The HEV had increased emissions of particles smaller than 23 nm under cold start, but similar overall PN emission values, compared to a warm start. The results of this work highlight the importance of controlling HEV PN emissions to limit human exposure to PN in urban environments where the majority of PN emissions occur. The sensitivity of HEV PN emission factors and PNSD to engine behaviour and, in turn, test cycle dynamic properties, is important to note when considering legislative test cycles, particularly with reference to the freedoms afforded by the RDE test cycle. The results also indicate that substantial improvements to air quality could be made by reducing the particle measurement protocol PN cut-off size to 10 nm.

Performance assessment of CORDEX regional climate models in wind speed simulations over Zambia

There is no single solution to cutting emissions, however, renewable energy projects that are backed by rigorous ex-ante assessments play an important role in these efforts. An inspection of literature reveals critical knowledge gaps in the understanding of future wind speed variability across Zambia, thus leading to major uncertainties in the understanding of renewable wind energy potential over the country. Several model performance metrics, both statistical and graphical were used in this study to examine the performance of CORDEX Africa Regional Climate Models (RCMs) in simulating wind speed across Zambia. Results indicate that wind speed is increasing at the rate of 0.006 m s− 1 per year. RCA4-GFDL-ESM2M, RCA4-HadGEM2-ES, RCA4-IPSL-CM5A-MR, and RCA4-CSIRO-MK3.6.0 were found to correctly simulate wind speed increase with varying magnitudes on the Sen’s estimator of slope. All the models sufficiently reproduce the annual cycle of wind speed with a steady increase being observed from April reaching its peak around August/September and beginning to drop in October. Apart from RegCM4-MPI-ESM and RegCM4-HadGEM2, the performance of RCMs in simulating spatial wind speed patterns is generally good although they overestimate it by ~ 1 m s− 1 in the western and southern provinces of the country. Model performance metrics indicate that with a correlation coefficient of 0.5, a root mean square error of 0.4 m s− 1, an RSR value of 7.7 and a bias of 19.9%, RCA4-GFDL-ESM2M outperforms all other models followed by RCA4-HadGEM2, and RCA4-CM5A-MR respectively. These results, therefore, suggest that studies that use an ensemble of RCA4-GFDL-ESM2M, RCA4-HadGEM2, and RCA4-CM5A-MR would yield useful results for informing future renewable wind energy potential in Zambia.

Biodegradable magnesium fuel-based Janus micromotors with surfactant induced motion direction reversal

The speed and motion directionality of bubble-propelled micromotors is dependent on bubble lifetime, bubble formation frequency and bubble stabilization. Absence and presence of bubble stabilizing agents should significantly influence speed and propulsion pattern of a micromotor, especially for fast-diffusing molecules like hydrogen. This study demonstrates a fully biodegradable Janus structured micromotor, propelled by hydrogen bubbles generated by the chemical reaction between hydrochloric acid and magnesium. Six different concentrations of hydrochloric acid and five different concentrations of the surfactant Triton X-100 were tested, which also cover the critical micelle concentration at a pH corresponding to an empty stomach. The Janus micromotor reverses its propulsion direction depending on the availability and concentration of a surfactant. Upon surfactant-free condition, the Janus micromotor is propelled by bubble cavitation, causing the micromotor to be pulled at high speed for short time intervals into the direction of the imploding bubble and thus backwards. In case of available surfactant above the critical micelle concentration, the Janus micromotor is pushed forward by the generated bubbles, which emerge at high frequency and form a bubble trail. The finding of the propulsion direction reversal effect demonstrates the importance to investigate the motion properties of artificial micromotors in a variety of different environments prior to application, especially with surfactants, since biological media often contain large amounts of surface-active components.

Ωbar in NGC 5597 from Very Large Array H i 21 cm Observations

We report Very Large Array B-configuration observations of the atomic hydrogen 21 cm line emission from the barred disk galaxy NGC 5597 at an angular resolution of ∼ 7.″1 × 4.″2. Using the resonance method, and assuming the ratio of the corotation radius to the semimajor axis of the stellar bar is unity (), we estimate the angular pattern speed of the stellar bar to be, Ωbar ∼ 15.3 km s−1 kpc−1. This constant value for Ωbar crosses Ωgas + κ(R)/4 at a distance ∼6.73 kpc, which would correspond to the spatial location of the north spiral structure near an outer m = 4 resonance. This value of Ωbar is similar to the values estimated for other bright nearby barred galaxies that exhibit circumnuclear rings (near inner Lindblad resonance) or outer rings (near outer Lindblad resonance).

A slow bar in the lenticular barred galaxy NGC 4277

Aims.We characterised the properties of the bar hosted in lenticular galaxy NGC 4277, which is located behind the Virgo cluster.Methods.We measured the bar length and strength from the surface photometry obtained from the broad-band imaging of the Sloan Digital Sky Survey and we derived the bar pattern speed from the stellar kinematics obtained from the integral-field spectroscopy performed with the Multi Unit Spectroscopic Explorer at the Very Large Telescope. We also estimated the co-rotation radius from the circular velocity, which we constrained by correcting the stellar streaming motions for asymmetric drift, and we finally derived the bar rotation rate.Results.We found that NGC 4277 hosts a short (Rbar = 3.2−0.6+0.9kpc), weak (Sbar = 0.21 ± 0.02), and slow (ℛ = 1.8−0.3+0.5) bar and its pattern speed (Ωbar = 24.7 ± 3.4 km s−1kpc−1) is amongst the best-constrained ones ever obtained with the Tremaine–Weinberg (TW) method with relative statistical errors of ∼0.2.Conclusions.NGC 4277 is the first clear-cut case of a galaxy hosting a slow stellar bar (ℛ &gt; 1.4 at more than a 1σconfidence level) measured with the model-independent TW method. A possible interaction with the neighbour galaxy NGC 4273 could have triggered the formation of such a slow bar and/or the bar could be slowed down due to the dynamical friction with a significant amount of dark matter within the bar region.

APPLICATION OF BOX-BEHNKEN, ANN, AND ANFIS TECHNIQUES FOR IDENTIFICATION OF THE OPTIMUM PROCESSING PARAMETERS FOR FDM 3D PRINTING PARTS

Fused Deposition Modeling, among the various 3D printing approaches, is becoming more and more popular because of its capacity to produce complicated parts quickly. The tensile strength of parts printed with polylactic acid (PLA) showed a significant variation of many factors such as printing speed, printing temperature, printing angle and infill pattern. This study presented an experimental investigation of collecting data with four input factors namely printing speed, printing temperature, printing angle and infill pattern with the tensile strength response. The research methodology of the RSM Box-Behnken DOE method, ANN (Artificial neural network), and ANFIS (Adaptive neuro-fuzzy inference systems) has been used to determine the optimum process 3D printing parameters. The obtained results based on RSM, ANN and ANFIS methods are used to predict the tensile strength of 3D printed FDM details. The best tensile value is 7,03303 MPa corresponding to print speed of 30,0003 mm/s, printing temperature of 211,594℃, printing angle of 90° with Honeycomb” infill printing pattern. Moreover, the results also highlighted that ANFIS is potential approach for forecasting the tensile strength of 3D printing parts more competitively.

Impacts of zonal winds on planetary oscillations and Saturn ring seismology

ABSTRACT The excitation of density and bending waves in Saturn’s C ring by planetary oscillation modes presents a unique opportunity to learn about gas giant interiors and rotation. However, theoretical complications related to Saturn’s rapid and differential rotation pose a barrier to the full utilization of ring wave detections. We calculate oscillation modes using a complete, non-perturbative treatment of differential rotation modelled after Saturn’s zonal winds in self-consistently computed, polytropic equilibria. We find that previous, approximate treatments of the effects of differential rotation in Saturn overestimate shifts in the frequencies of fundamental modes (f modes) thought to be responsible for the majority of the waves detected in the C ring, due to an omitted modification of the equilibrium shape and structure of the planet by differential rotation. The bias introduced by these frequency overestimates is small, but significant relative to the uncertainties afforded by Cassini data. We additionally consider the non-perturbative effects of Saturn-like differential rotation on the rotational mixing of f modes and internal gravity modes (g modes), which is relevant to detections of multiple density waves with very closely split pattern speeds. We find that higher-order rotational effects can produce orders-of-magnitude enhancements in the surface gravitational perturbations of g modes dominated by large spherical harmonic degrees ℓ, regardless of frequency separation from the sectoral f mode. Despite this enhancement, we find that the observed fine splitting of density waves is unlikely to involve g modes dominated by ℓ ≳ 10. This restriction may aid in the inference of possible internal structures for Saturn.

Spatio-Temporal Analysis of Valley Wind Systems in the Complex Mountain Topography of the Rolwaling Himal, Nepal

The diurnal, seasonal, and spatio-temporal characteristics of local wind systems in a steep mountain valley in Nepal are analyzed with the identification of valley wind days (VWDs). Distributed across the Rolwaling Himal valley in Nepal between 3700 and 5100 m a.s.l. at eight automated weather stations (AWSs), meteorological data between October 2017 and September 2018 were examined. VWDs were classified by means of ERA5 reanalysis data and in situ observations, employing established thresholds using precipitation, solar radiation, air pressure, and wind speed data at different pressure levels. Thus, overlying synoptic influences are highly reduced and distinctive diurnal patterns emerge. A strong seasonal component in near-surface wind speed and wind direction patterns was detected. Further analyses showed the diurnal characteristics of slow (approximately 0.5–0.9 m s−1), but gradually increasing wind speeds over the night, transitional periods in the morning and evening, and the highest averaged wind speeds of approximately 4.3 m s−1 around noon during the VWDs. Wind directions followed a 180∘ shift with nocturnal katabatic mountain winds and inflowing anabatic valley winds during the daytime. With AWSs at opposing hillsides, slope winds were clearly identifiable and thermally driven spatio-temporal variations throughout the valley were revealed. Consequently, varying temporal shifts in wind speed and direction along the valley bottom can be extracted. In general, the data follow the well-known schematic of diurnal mountain–valley wind systems, but emphasize the influence of monsoonal seasonality and the surrounding complex mountain topography as decisive factors.

Riemannian classification analysis for model EEG intention speed patterns.

In this paper, the paradigm of the intention of speed changes from EEG signals with Riemannian classifiers methods is studied in 10 subjects. In addition, the best frequency band and how different electrode configurations affect the accuracy of the model are analyzed. In the prediction of the intention to change speed, results of 68.6% were obtained, in the one of only Increase, results of 64.41 % were obtained, and in the one of only Decrease, results of 71.5% were obtained.

A slow lopsided bar in the interacting dwarf galaxy IC 3167

ABSTRACT We present surface photometry and stellar kinematics of IC 3167, a dwarf galaxy hosting a lopsided weak bar and infalling into the Virgo cluster. We measured the bar radius and strength from broad-band imaging and bar pattern speed by applying the Tremaine–Weinberg method to stellar-absorption integral-field spectroscopy. We derived the ratio of the corotation radius to bar radius (${\cal {R}}=1.7^{+0.5}_{-0.3}$) from stellar kinematics and bar pattern speed. The probability that the bar is rotating slowly is more than twice as likely as that the bar is fast. This allows us to infer that the formation of this bar was triggered by the ongoing interaction rather than the internal processes.

Influence of process parameters on mechanical strength, build time, and material consumption of 3D printed polylactic acid parts

AbstractThe purpose of the study is to examine and analyze the effect of different process parameters of fused deposition modeling process, namely, nozzle diameter, build orientation, infill density, raster pattern, layer height, and print speed on the response variables, namely, tensile strength, build time, and material consumption. Taguchi L27 orthogonal array experimental design has been adopted to print the PLA samples for experimental investigation. The optimum values of process parameters are obtained from the signal‐to‐noise ratio values of responses. The performed confirmation tests revealed that optimum process parameters combination determined through Taguchi method improves the tensile strength, reduce the build time, and material consumption significantly. Confirmation from analysis of variance (ANOVA) results revealed that the build orientation and nozzle diameter are the most influential process parameters for all the considered responses. The infill density is found to be an influential process parameter for material consumption. Further, the developed regression models for prediction of response characteristics and normal probability plots show significance of coefficients for predicted models. Results from the confirmation test revealed that the PLA part printed with optimum settings ((Nd)3‐(Bo)3‐(Id)3‐(Rp)1‐(Lh)2‐(Ps)1)) for tensile strength shows maximum tensile strength of 61.24 MPa with an improvement of 6.26%. Similarly, the part printed with the optimum settings ((Nd)3‐(Bo)1‐(Id)2‐(Rp)1‐(Lh)3‐(Ps)3) for build time takes 0.32 h of time with a reduction of 8.57%. The part printed with the optimum settings ((Nd)1‐(Bo)1‐(Id)1‐(Rp)2‐(Lh)1‐(Ps)2) for material consumption consumes material of 7.6 g with a reduction of 2.56%. Fracture mechanics results depict that variation of process parameters during the fabrication of samples has significant influence on the tensile strength.