Aluminum Alloy AA Research Articles

Formability analysis of self-piercing riveted dissimilar joint of B1500HS steel and AA5052 aluminum alloy

Formability analysis of self-piercing riveted dissimilar joint of B1500HS steel and AA5052 aluminum alloy

High-fidelity prediction of forming quality for self-piercing riveted joints in aluminum alloy based on machine learning

The effect of rivet length and sheet thickness on the cross-sectional formation and tensile-shear performance of self-piercing riveted joints in AA5754 aluminum alloy was examined through experimental investigation. The influence degree of joining parameters on the forming quality was analyzed. It was revealed that rivet length and sheet thickness are pivotal factors influencing the tensile-shear strength of the joint, culminating in the identification of four optimal riveting process schemes:LCh1Ah2A、LAh1Ah2B、LAh1Ah2B and LBh1Ah2B. A simulation model for self-piercing riveting was established, employing the GISSMO failure model and the modified Mohr-Coulomb (MMC) failure criteria to predict the damage and fracture of the aluminum alloy. A plethora of high-quality datasets depicting the cross-sections of the joints were derived from simulation analysis. Subsequently, the structure and hyperparameter determination method of traditional neural network prediction models were elucidated. By amalgamating the Aquila Optimization (AO) algorithm with the African Vultures Optimization Algorithm (AVOA), a hybrid optimization algorithm model known as MIC_AOAVOA was developed. This model effectively harnesses the strengths of various algorithms to augment search efficiency and optimization capabilities. Strategies for population initialization and adaptive weight adjustments were incorporated to enhance the algorithm's convergence velocity and the quality of solutions. The cauchy opposition-based learning (COBL) and fitness-distance balance (FDB) strategy further refined the composite algorithm, bolstering its global search capabilities and population diversity. Comparative analyses were performed with single algorithm models and traditional BP neural network models, with an in-depth examination of the MIC_AOAVOA_BP model's prediction outcomes. Comprehensive evaluations utilizing error statistics and composite evaluation indicators demonstrated that the model consistently achieved mean absolute percentage error (MAPE) values below 10%, correlation coefficients (R²) exceeding 0.98, and stable mean squared error (MSE) values around 0.0002 across the prediction of three metrics. These results underscore the model's high precision and stability. Consequently, the proposed enhanced model offers a solution that is more stable, accurate, and robust for the prediction of forming quality in self-piercing riveted joints within engineering applications.

Effects of multi-objective optimization of friction stir welding process parameter on mechanical and ballistic properties of AA5754 aluminum alloy

Friction stir welding (FSW) is a solid-state welding process commonly used to join similar and dissimilar aluminum alloys. This study aims to investigate multi-criteria decision-making, multi-objective optimization, Taguchi’s L9 design of experiments, and the technique for order preference by similarity to the ideal solution (TOPSIS) to evaluate the effects of various FSW parameters specifically, welding speed, feed, and axial load on the mechanical properties of AA5754 aluminum alloy. Following the enhancement of the welding parameters, an analysis of variance (ANOVA) was performed to identify the most influential parameter in the FSW process. The findings indicated that tensile strength, impact strength, and microhardness were predominantly affected by welding speed (94.82%), feed (3.12%), and axial load (1.32%), respectively. With a hexagonal tool and optimal process parameters of feed (20 mm/min), axial load (7 kN), and speed (1200 rpm), the joint obtained the maximum microhardness (81 HV), impact strength (3.01 J/mm2), and tensile strength (163.89 MPa). The microstructure and X-ray diffraction analyses indicated that the crystals were tiny, with higher dislocations in the stir zone, indicating improved mechanical properties. In the FSW joint, dimples and voids were observed on the tensile and impact fracture surfaces. Finally, the ballistic properties of the optimized AA5754 FSW joint were determined. An asymmetric V-shaped deformation profile was observed around the impact point, with the highest deformation at the center. An increase in impact velocity from 134 to 187.6 m/s did not result in significant differences in the deformation of the FSW joint. The fracture surfaces of ballistic-tested friction stir welded joints exhibited shear regions and localized bands.

Experimental and computational studies on hot cracking in single laser tracks of aluminium alloy AA2024 and related implications for laser powder bed fusion

Laser powder bed fusion of high-strength aluminium alloys remains challenging due to the formation of hot cracks during the printing process. Hot cracking is a complex phenomenon involving a complex thermo-mechanical and metallurgical interplay. Such relationship needs to be fully understood to reap the benefits of advanced laser modulation (temporal and spatial) capabilities, now becoming available in PBF-LB. To this end, we explore the formation of hot cracks in single tracks produced using a simple spatial–temporal laser modulation characterised by laser pulses of various distance. The formation of cracks is then rationalised by physical and numerical modelling using multi-physics CFD simulation. We demonstrate that the area of the mushy zone at the back of the moving melt pool, dynamically contracts and expands according to the laser temporal regimes and find maxima in correspondence to the largest laser pulse distance and the time steps between exposures. By then analysing in detail in the crack observed in the printed parts fabricated with the same laser modulation, it is possible to conclude that the mechanisms leading to hot cracks in these specimens is analogous. In turn, the insights on single tracks can be extended, for the most part, to the case of bulk specimens. Nevertheless, printed specimens appear to be more sensitive to the erratic movement of the melt pool, due to the presence of a larger number of highly energetical grain boundaries and unintended microstructural defects (voids and inclusions), from which cracks can nucleate.Graphical

Investigation of wear and transverse rupture strength of AA2219/ZrO2/B4C hybrid composite materials prepared with 3D ball mixer and produced by spark plasma sintering

ABSTRACT Aluminum alloys have advanced to meet the growing demand for strong, lightweight materials. The 2219 aluminum alloy has gained popularity due to its superior mechanical properties and high copper content. However, despite these improvements, the wear characteristics of metal matrix composites with ceramic reinforcements have been suboptimal. This study aims to develop metal matrix composites that improve the mechanical and wear properties of AA2219 aluminum alloy. A homogeneous mixture was created using a 3D mechanical mixer/miller apparatus. ZrO2 and B4C reinforcements were added to the matrix in ratios of 5%, 10%, and 15%, including hybrid composites with both reinforcements. Mechanical and wear characteristics were analyzed, and a 3D profilometer was used to evaluate wear properties and determine tribological parameters. The results showed that the pulverized reinforcement particles were uniformly dispersed within the matrix. The sample with a hybrid reinforcement comprising 15% of the total composition exhibited the highest hardness, measuring 164.96 hV. This study demonstrates that incorporating ceramic reinforcements in specific ratios can significantly enhance the mechanical and wear properties of 2219 aluminum alloy composites.

INVESTIGATION ON THE STRENGTH OF E-GLASS FIBER/AA5052-H32 FIBER METAL LAMINATES CONNECTED USING RIVETED JOINTS

Fiber metal laminates (FMLs) belong to a class of composite materials comprising layers of metal sheets and fiber-reinforced polymers (FRP), configured in a specific sequence. This study investigates the tensile strength of FML specimens joined by riveted joints. FML plates were fabricated using AA5052 aluminium alloy, E-glass fibers, epoxy resin, and layered double hydroxide (LDH) via a hand layup process. The experimental parameters included the pattern of rivets, type of rivet materials, and rivet size. Tensile strength, the output response, was evaluated using Taguchi’s L9 orthogonal array design, followed by testing on a universal testing machine. The main effect plot and 3D surface plots were employed to analyze the tensile test results. Maximum tensile strength was held by the test specimen which was connected by the rivets made up of mild steel. From the ANOVA results presented in Table 6 , it was inferred that the number of rivets used for joining the FML specimens (pattern) played a major role in deciding the tensile strength of the specimens (57.25%). A regression equation, derived from Design Expert software, established the relationship between input variables and the tensile strength of FML specimens. ANOVA was conducted to assess the impact of each process variable on achieving optimal tensile strength. This research contributes novelty by integrating LDH into FML fabrication and demonstrates practical significance through systematic optimization of riveting parameters to enhance tensile strength. Quantitative and qualitative analyses underscore the effectiveness of the proposed FML configuration, validating its potential for structural applications.

Improvement of Hardness on Butt Weld Joints Aluminium Alloy AA 6061 Using the Underwater Friction Stir Weld (UFSW) Method

This study reveals the hardness improvement resulting from Underwater Friction Stir Welding (UFSW) on the butt joint method AA 6061. Underwater welding introduces complexity to the joint's hardness due to the presence of water, which affects the welding process and the quality of the joint formed. The objective of the UFSW study is to explore potential advantages in the aquatic environment, primarily to obtain the optimal machine tilt angle. The study used a conventional milling machine with various spindle speeds, feed rates, and tilt angles to get the best combination of parameters. The spindle speed of 750 rpm, welding speed of 20 mm/min, and machine head angle of 2° recorded show the Brinell hardness (HRB) of UFSW to be 98.8% better than Friction Stir Welding (FSW) on various parameters. This study revealed that a machine tilt angle of 2° increased the hardness of UFSW welding. Theresults show that UFSW can increase HRB through proper head tilt angle, which is even better than the existing method, which is FSW.

Surface chemistry characterization of AA2014 aluminum alloy powder through triboelectric charging

Traditional characterization techniques for powders primarily focus on bulk properties, often neglecting the critical role of surface chemistry variations that influence the performance in applications such as additive manufacturing. The method presented in this work addresses this gap by utilizing triboelectric charging concept to gain a comprehensive understanding of powder surface state under varying environmental conditions. In particular, the study investigates the detection of surface chemistry variations of AA2014 powder caused by an exposure to various relative humidity (RH) levels through a change in triboelectric charging behavior. The surface variations are analyzed in parallel with X-ray photoelectron spectroscopy (XPS). The findings reveal a direct correlation between elevated RH and increased hydroxide species content at the surface of the powder. The triboelectric charging experiments demonstrated a significant RH-dependent variations of charge accumulation, with higher humidity levels leading to reduced static charge buildup on the powder particles. The charge accumulation behavior in the powder was fitted with the compressed exponential relaxation model. The results showed that each surface chemical species exhibits a distinct correlation between charging rate and charge accumulation, confirming the effectiveness of the method to detect subtle variations in surface chemistry. The variations in the exponent of the fitted model were shown to be characteristics to the surface scale of the powder particles.

Effect of Alkaline Etching on Formation Behavior and Corrosion Resistance of a Cr-Zr-Ti TCP Conversion Coating on AA2024 Aluminum Alloy

Trivalent chromium process conversion coating is considered to be the ideal alternative to traditional chromate conversion coating due to its high corrosion resistance and low toxicity. However, achieving a high corrosion resistance trivalent chromium conversion coating on 2xxx aluminum alloys has been a great challenge. Herein, based on a newly developed trivalent chromium conversion solution (CN patent, ZL 202210804263.2), the effect of alkaline etching on the formation behavior and corrosion resistance of the coating on AA2024-T351 aluminum alloy was investigated. It was found that under the same conditions, the mechanically polished sample and the sample alkaline etched for 30 s showed the highest corrosion resistance. When the alkaline etching time was too short or too long, the corrosion resistance of the coating deteriorated. This is ascribed to changes in the surface microstructure of the alloy during alkaline etching, i.e., reduced number of intermetallic particles and formation of a copper enrichment layer. Reducing the number of intermetallic particles on the alloy surface is beneficial for uniform growth of the coating. However, the copper enrichment layer participated in formation of the coating, resulting in doping of copper species in the coating, which is detrimental to the corrosion resistance of the coating.

Achieving microstructural homogeneity in the stir zone across thick AA6061 welds using self-reacting bobbin tool friction stir welding

This study focuses into strategizing the usage of self-reacting bobbin tool friction stir welding (SRBT-FSW) to obtain consistent microstructural homogeneity along the thickness of AA6061 aluminium alloy (AA) thick plates during welding. The SRBT-FSW technology, distinguished by its dual-shoulder design, represents a significant step forward in FSW by eliminating the requirement for a backing anvil and promoting balanced heat distribution. This study seeks to address the issues of maintaining uniform microstructural characteristics throughout the weld zone, which is crucial for the mechanical performance and durability of welded joints in structural applications. The experimental study entails the systematic welding of AA6061 plates of 6 mm thickness using a self-reacting bobbin tool under a fixed processing condition. Electron backscatter diffraction (EBSD) was used to characterize the grain structure and phase distribution over the weld. Mechanical parameters like as tensile strength and hardness were determined to establish correlations between microstructure and mechanical performance. The results demonstrated that SRBT-FSW significantly enhances microstructural homogeneity across the weld zone, leading to improved mechanical properties. In the Bottom Zone (BZ), a refined grain structure with an average grain size (AGS) of 3.53 µm and a random or weak texture was observed, contributing to enhanced hardness and mechanical performance, with an ultimate tensile strength (UTS) of 220 MPa. In contrast, the Top Zone (TZ) exhibited a coarser AGS of 4.33 µm with a pronounced {111} crystallographic texture, resulting in a slightly lower UTS of 205 MPa. The Middle Zone (MZ), influenced by the greater heat input from both the TZ and BZ, showed an intermediate AGS of 3.99 µm, predominantly oriented along the {101} plane, and achieved a UTS of 194 MPa, with a slight reduction in ductility. This study highlights the potential of self-reacting bobbin tool friction stir welding as a reliable method for making high-quality, homogeneous welds in thick aluminium plates and paving way for their wider application in the aerospace, automotive, and shipbuilding industries, where homogeneous microstructural qualities are of significant importance.

High-Velocity Impact Response of Directly Recycled Aluminium Alloy AA6061 Plates

High-Velocity Impact Response of Directly Recycled Aluminium Alloy AA6061 Plates

Investigation of the Process Parameters in Rotary Friction Welded Dissimilar AA7075/AA5083 Aluminum Alloy Joints on Fatigue Initiation using FEA and ANN

The rotary friction welding (RFW) method is one of the most widespread methods in the world for producing bimetallic components that require high mechanical strength. Simulations play a vital role in improving energy efficiency and reducing environmental impact, aligning with the sustainability goals of modern industry. A neural network (NN)-based incremental learning system was developed to predict crack growth and fatigue for AA5083 and AA7075 aluminum alloys. The results indicate the ability of this method to accommodate the input temperatures and the S-N curve and provide reliable predictions of expected fatigue. This method can reduce labor costs and time spent on crack propagation tests, enhancing the effectiveness of production processes and reducing process costs. This work also reveals the ability of neural . It maynetworks (NN) in monotonic function extrapolation like the S-N curve, which may pave the way for a wide variety of monotonic function-predicting problems. In future studies, a neural network (NN)-based increment learning scheme could be trained with random parts of individual S–N curves and applied to predict the rest. Additionally, the verification utilizing AISI 2205 and AISI 1020 steel has observed that neural networks may obtain S-N curve values for another metal with less than an 8% error rate. Friction pressure increases temperature, deformation, and stress in welding processes. Friction pressure 17 MPa increases temperature to 355 degrees Celsius, while Friction pressure 23 MPa increases deformation to 0.020 mm. A friction pressure of 29 MPa increases equivalent stress to 110 MPa. The indication of the S-N curve shows that increasing welding pressure increases Alternating Stress. Friction pressure also increases life, with minimum life cycles reaching 171040 cycles at 17 MPa, 195560 cycles at 23 MPa, and 283690 cycles at 29 MPa. Comparing research and simulation results, convergence is less than 8%, reducing error.

Effect of high pressure-low plasticity burnishing on the mechanical and microstructural behaviour of copper foil interlayered FSW aluminium alloys

Abstract This study delves into the impact of high pressure-low plasticity burnishing (HP-LPB) on the mechanical and microstructural behaviour of friction stir welding (FSW) joints, specifically involving AA5052 and AA6082 aluminium alloys. Notably, copper foil (CF) is introduced as a novel element in the HP-LPB process to enhance the weld strength. The experiments were conducted with the tool rotational speeds (TRS) of 1000, 1100, and 1200 RPM, each paired with the welding speeds (WS) of 20, 25, and 30 mm min−1, and tool tilt angle (TTA) of 0°, 1°, and 2°. Mechanical behaviour is assessed through tensile testing along with microhardness measurements, revealing the advantages of HP-LPB with CF in enhancing joint strength and toughness. The microstructural analysis reveals the dissolution of precipitates, highlighting the influential role of copper foil in the improvement of joint efficiency. From the weld without a CF interlayer, a maximum tensile strength of 188 MPa was achieved at a TRS of 1200 RPM, WS of 25 mm min−1 and TTA of 2°. The post-processed FSW sample interlayered with copper foil, exhibited an improvement in joint efficiency by 87% at the optimum process parameter. This research demonstrates that the use of copper foil interlayers combined with HP-LPB treatment can substantially enhance the mechanical properties and structural integrity of FSW aluminum alloys, offering a valuable solution for advanced industrial applications.

Enhancement of Mechanical Properties and Microstructure of Aluminium alloy AA2024 By adding TiO2 Nanoparticles

Modern engineering applications, especially in the automotive and aerospace industries, require essential and appealing properties such as lightweight with high strength and resistance. The key objective of the present study is to investigate the effect of TiO2 nanoparticles on the microstructure, impact strength, hardness and wear resistance of the stir cast aluminum alloy AA2024, An aluminium alloy was reinforced with different mass fractions (0 %, 2.5 %, 5 %, 7.5 %) of titanium dioxide nanoparticles by stir casting followed by solution annealing at 500°C for 3 h, quenching in water and aging at 175°C for 3 h. Results showed that regular morphology and fine grain size of primary AA2024 particles are achieved after the addition of 2.5 wt.% TiO2 compared to the sample without the addition of nanoparticles composite. In addition, it was found that adding nanoparticles increased energy absorption, and this effect is improved by increasing impact strength by adding nanoparticles, the impact strength increased from 5 j/m2 to 7 j/m2 at 5%. At the same time, the increase of nanoparticles effect decreases the mass losses (increase in wear resistance). With a weight fraction of 5 wt.% TiO2, the alloy exhibits the highest value of hardness.

Elucidating the effect of strain path-dependent crystallographic texture evolution on the electrochemical behavior of nanostructured AA2024 aluminum alloy

This research provides insight into the effect of strain path-dependent texture evolution on the electrochemical behavior of nanostructured AA2024 aluminum alloy in a phosphate buffer solution (pH = 8.3). To achieve this, AA2024 alloy sheets were processed using two methods: accumulative roll bonding (ARB) and cross accumulative roll bonding (CARB), i.e., rotating the sheets 90° around the normal direction (ND) axis between each cycle. The ARB-processed AA2024 alloy exhibited a pancake-shaped structure and included texture components of Copper {112}<111>, Brass {011}<211>, P {110}<221>, and S {123}<634>. Meanwhile, the CARB-processed AA2024 alloy had extremely fine and equiaxed nano-grains (< 100 nm) and texture components of S {123}<634>, Brass {011}<211>, Goss {011}<100>, Rotated Cube {001}<110>, and P {110}<221> after eight cycles. Electrochemical studies demonstrated an increase in corrosion current density due to high imposed strains in the ARB route, which in effect made the conditions of passive layer formation more difficult and lowered the corrosion resistance. Additionally, achieving a more uniform distribution of extremely fine grains and {011} orientation textures such as Brass {011}<211>, Goss {011}<100>, and P {110}<221> texture components in the CARB route, provided ideal conditions for forming oxide passive films with superior protection properties compared to ARB. These unique findings can contribute to the broader application of crystallographic-orientation-dependent electrochemical behavior of alloys in the field of corrosion management.

Parametric analysis of electrical discharge machining on AA6061 with a WC–Cu composite electrode

The AA6061 aluminium alloy surface characteristics presented in this study were obtained after it was machined using die sinking electro discharge machining (EDM) with a composite electrode developed through powder metallurgy. Machining was performed using negative polarity. In order to obtain optimum material removal rate (MRR) and surface roughness (SR), the research has been carried out, and EDM parameters like voltage, current and pulse on time were optimized using the response surface methodology that integrates the central composite design. The parameter interaction effects on EDM machined surface characteristics were studied with the aid of ANOVA. It was determined from model that the regression for MRR and SR were 98.6% and 98.3% respectively, means empirical model is considered sufficient. It was observed that increased MRR and SR were observed in the condition of increased current, but MRR and SR decreased at increased voltage and pulse on time. This could be due to strengthened ionization temperature that increased MRR with acceptable SR. The microstructure of the machine was assessed using microscopic evaluation. The increased current contributed to the formation of a recast layer and debris which hinders the machining process and reduces MRR. The experimental results show that the maximum MRR of 0.087 mg/min and minimum SR of 1.893 µm were achieved. Additionally, the use of WC–Cu composite electrodes led to an increase in hardness from 65 HV to 78 HV in the machined region. It is concluded that WC–Cu composite electrodes typically result in higher hardness, improved MRR and better SR for the AA6061 alloy compared to conventional Cu electrodes.

Center-Punching Mechanical Clinching Process for Aluminum Alloy and Ultra-High-Strength Steel Sheets

In recent years, with the rapid advancement of automotive lightweight technology, the mechanical clinching process between aluminum alloy and ultra-high-strength steel sheets has received extensive attention. However, the low ductility of ultra-high-strength steel sheets often results in conventional mechanical clinching processes producing joints that either fail to establish effective interlocks or cause the steel sheets to fracture. To address this issue, a novel mechanical clinching process is presented, called center-punching mechanical clinching (CPMC). This innovative process employs a method of punching, flanging, and bulging gradation to achieve the mechanical clinching of aluminum alloy and ultra-high-strength steel sheets in a single step. In order to determine the effects of different parameters on the quality and strength of the joint, an experimental study was carried out for various die depths and diameters based on the condition of constant punch size. Based on tensile and shear tests, the static strength and failure modes of CPMC joints were analyzed. The results indicated that the CPMC process significantly enhances the connectivity of joints for AA5052 aluminum alloy and DP980 ultra-high-strength steel. Optimal tensile and shear strengths of 1264 and 2249 N, respectively, were achieved at a die depth of 2.2 mm and a diameter of 10.4 mm. The CPMC process provides new ideas for the mechanical clinching of aluminum alloy and ultra-high-strength steels.

Analyzing the Influence of Titanium Content in 5087 Aluminum Filler Wires on Metal Inert Gas Welding Joints of AA5083 Alloy

As the demand for lightweight structures in the transportation industry continues to rise, AA5083 aluminum alloy has become increasingly prominent due to its superior corrosion resistance and weldability. To facilitate the production of high-quality, intricate AA5083 components, 5087 aluminum filler wire is commonly utilized in metal inert gas (MIG) welding processes for industrial applications. The optimization of filler wire composition is critical to enhancing the mechanical properties of AA5083 MIG-welded joints. This study investigates the effects of modifying 5087 aluminum filler wires with different titanium (Ti) contents on the microstructure and weldability of AA5083 alloy plates using MIG welding. The influence of Ti contents was systematically analyzed through comprehensive characterization techniques. The findings reveal that the constitutional supercooling induced by the Ti element and the formation of Al3Ti facilitate the heterogeneous nucleation of α(Al), thereby promoting grain refinement. When the Ti content of 5087 filler wire is 0.1 wt.%, the grain size of the weld center was 78.48 μm. This microstructural enhancement results in the improved ductility of the AA5083 MIG-welded joints, with a maximum elongation of 16.64% achieved at 0.1 wt.% Ti addition. The hardness of the joints was the lowest in the weld center zone. This study provides critical insights into the role of Ti content in MIG welding and contributes to the advancement of high-performance filler wire formulations.

Investigation of an L-Shaped Cross-Sectioned AA6061 Aluminum Alloy Ring via Extrusion and Self-Bending Integral Processing Technology

Investigation of an L-Shaped Cross-Sectioned AA6061 Aluminum Alloy Ring via Extrusion and Self-Bending Integral Processing Technology

Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.